13 Forecasting Jobs in Bangalore (Bengaluru) | Forecasting Job openings in Bangalore (Bengaluru)

Key Responsibilities

 Strong understanding of Machine Learning algorithms (supervised and unsupervised)

 Hands-on experience with Deep Learning frameworks (TensorFlow, PyTorch, or similar)

 Experience in NLP techniques and libraries (NLTK, spaCy, Hugging Face, etc.)

 Solid knowledge of Statistics, probability, and data analysis methods

 Proficiency in SQL for querying relational databases

 Strong programming skills in Python (or similar languages)

 Excellent communication skills with the ability to explain complex concepts simply

Required Qualifications

 3+ years of hands-on experience as a Data Scientist or in a similar role.

 Strong expertise in classical machine learning and regression modeling.

 Solid understanding of statistics, including probability, distributions, hypothesis testing,

and correlation analysis.

 Proficiency in Python with libraries such as: scikit-learn pandas NumPy

 Experience working with structured/tabular data.

 Strong problem-solving and analytical thinking skills.

 Ability to clearly explain models and results to non-technical stakeholders.

About the Role

We are looking for a high-energy, consultative, and commercially driven Account Executive – Microsoft Azure to accelerate Comprinno's Azure business.

This is a new-business acquisition and revenue-growth role. The Account Executive will identify, develop, qualify, and close Azure-led opportunities across mid-market, digital-native, and enterprise customers. The role will work closely with Microsoft, Comprinno's Partnerships team, Presales, Cloud Engineering, Data & AI, Managed Services, Marketing, and executive leadership.

The ideal candidate should understand enterprise technology sales and be capable of engaging CIOs, CTOs, Engineering leaders, Infrastructure leaders, Data/AI leaders, and business stakeholders around transformation initiatives.

This is not a transactional cloud-reselling role. We are looking for someone capable of developing consultative, multi-service customer relationships.

Role Charter

The Account Executive owns:

Prospect → Discover → Qualify → Shape → Propose → Negotiate → Close → Handover

The primary objective is:

Acquire new Azure customers and maximize the strategic value of every new customer relationship.

The Account Executive owns the commercial opportunity and closure.

Presales and Engineering own deep technical solutioning.

Customer Success owns post-sale retention and expansion following successful handover.

Key Responsibilities

1. Azure Business Development

• Build and execute a territory and account strategy for Comprinno's Azure business.
• Identify new-logo opportunities across target customer segments.
• Develop opportunities through:
• Direct prospecting
• Marketing-generated leads
• Microsoft referrals and co-sell
• Partner ecosystem
• Events and industry networks
• Existing executive relationships
• Build a healthy pipeline capable of consistently achieving revenue targets.
• Identify organizations undergoing cloud adoption, migration, modernization, Data/AI transformation, or infrastructure optimization.
• Develop multi-threaded relationships within target accounts.

2. Consultative Enterprise Selling

Engage customers around business and technology outcomes rather than individual Azure services.

Understand:

• Business objectives
• Existing technology landscape
• Cloud strategy
• Application portfolio
• Infrastructure challenges
• Security requirements
• Data & AI priorities
• Cost challenges
• Availability and resilience requirements
• Modernization roadmap

Translate those conversations into qualified opportunities for Comprinno.

Build relationships with decision-makers and influencers across CIO, CTO, CISO, Engineering, Infrastructure, Cloud, Data/AI, Procurement, and Finance functions.

3. Azure Solution Sales

Develop opportunities across Comprinno's Azure portfolio, including:

• Azure Cloud Migration
• Application Modernization
• Database Modernization
• Cloud-Native Engineering
• DevOps & Platform Engineering
• Kubernetes & Containerization
• Azure Managed Services
• Cloud Security & Compliance
• FinOps / Cost Optimization
• Disaster Recovery & Business Continuity
• Data Engineering & Analytics
• AI / Generative AI
• Agentic AI
• Cloud Consulting & Assessments

The AE is not expected to be a Solution Architect, but must possess sufficient technical understanding to conduct credible discovery conversations and identify when specialist technical involvement is required.

4. Microsoft Co-Sell & Ecosystem Engagement

• Build strong working relationships with relevant Microsoft field sellers, partner teams, solution specialists, and account teams.
• Identify joint account opportunities and participate in account mapping.
• Develop Microsoft-sourced and Microsoft-influenced pipeline.
• Work closely with Comprinno's Strategic Partnerships & Ecosystem team on joint GTM initiatives.
• Leverage appropriate Microsoft partner programs, marketplace opportunities, incentives, and funding mechanisms.
• Participate in joint customer meetings, workshops, events, and campaigns.
• Maintain disciplined follow-up on partner-generated opportunities.

The objective is to turn the Microsoft relationship into a repeatable customer-acquisition channel, not simply maintain partner engagement.

5. Opportunity Qualification

Apply disciplined qualification before significant technical and organizational resources are committed.

Establish:

• Customer problem
• Business impact
• Technical need
• Decision criteria
• Budget/commercial viability
• Decision-making stakeholders
• Competition
• Procurement process
• Expected timeline
• Next actions

Disqualify weak opportunities early and focus resources on opportunities with meaningful closure potential.

6. Opportunity Shaping & Solution Development

• Bring Presales and Engineering teams into qualified opportunities at the appropriate stage.
• Coordinate customer discovery workshops.
• Ensure technical teams clearly understand customer objectives and commercial context.
• Help shape solutions around business outcomes rather than technology alone.
• Coordinate assessments, workshops, POCs, proposals, and solution presentations.
• Ensure proposed solutions align with customer expectations, commercial realities, and Comprinno's delivery capabilities.

7. Commercial Ownership & Closure

Own the commercial lifecycle through closure.

• Develop proposals and commercial strategy.
• Coordinate pricing with internal stakeholders.
• Lead commercial negotiations.
• Navigate customer procurement processes.
• Coordinate SOWs, contracts, NDAs, and commercial approvals.
• Maintain momentum across complex buying cycles.
• Identify and resolve barriers to closure.
• Ensure opportunities have clear next actions and owners.

The AE remains accountable until the business is commercially closed, rather than treating proposal submission as the end of the sales process.

8. Pipeline & Forecast Management

• Maintain accurate opportunity information in HubSpot.
• Build sufficient pipeline coverage against quota.
• Maintain realistic close dates and opportunity stages.
• Conduct regular pipeline reviews.
• Forecast revenue accurately.
• Identify stalled opportunities and develop recovery strategies.
• Maintain clear next steps for every active opportunity.
• Ensure HubSpot remains the single source of truth for sales activity.

9. Land-and-Expand Strategy

The initial Azure engagement should be viewed as the beginning of a broader customer relationship.

Identify potential customer lifecycle paths such as:

Migration → Modernization → Managed Services → Security → Resilience → Data & AI

or

Data/AI → Cloud Modernization → Platform Engineering → Managed Services

The AE should establish the broader account potential during the acquisition process and capture it as part of the account strategy.

Following successful onboarding, expansion ownership transitions to the Customer Success organization.

10. Sales-to-Customer-Success Handover

• Ensure structured handover after customer acquisition.
• Transfer customer context, stakeholders, commitments, commercial terms, risks, and identified future opportunities.
• Introduce the Account Manager – Customer Success as the long-term commercial relationship owner.
• Remain engaged during the transition where executive or relationship continuity is required.

The objective is to create a seamless:

AE → Delivery → Customer Success

customer experience.

Required Qualifications & Skills

• Bachelor's degree in Engineering, Technology, Business, Management, or related discipline.
• 5–8 years of B2B technology sales experience, preferably in Cloud, IT Services, Digital Transformation, SaaS, Infrastructure, Data, or Security.
• Demonstrated experience acquiring new enterprise or mid-market customers.
• Experience carrying and achieving revenue or bookings targets.
• Experience managing complex B2B sales cycles involving multiple stakeholders.
• Strong understanding of cloud computing and enterprise technology.
• Working knowledge of Microsoft Azure and the Microsoft technology ecosystem.
• Ability to engage credibly with CIO/CTO/VP/Director-level stakeholders.
• Strong discovery, qualification, negotiation, and closing skills.
• Experience coordinating Presales and technical teams during sales cycles.
• Strong commercial acumen.
• Excellent communication, presentation, and executive-engagement skills.
• Strong CRM and forecasting discipline.
• Entrepreneurial mindset and bias for execution.

Desired Qualifications & Skills

• Previous experience selling Azure consulting, migration, modernization, or managed services.
• Experience working for a Microsoft Partner, cloud consulting company, MSP, or systems integrator.
• Existing relationships within the Microsoft field organization are highly desirable.
• Experience with Microsoft co-sell and partner-led GTM.
• Exposure to Azure Marketplace and Microsoft partner programs.
• Experience selling Data, AI, Generative AI, Security, DevOps, or Managed Services.
• Understanding of cloud economics and FinOps.
• Microsoft Azure Fundamentals or other Microsoft certifications are advantageous.
• MBA or equivalent business qualification is advantageous but not mandatory.

What We're Looking For

We are looking for someone who:

• Is fundamentally a hunter and new-business builder.
• Can open doors rather than depending entirely on inbound leads.
• Understands consultative technology selling.
• Is technically curious without trying to become the Solution Architect.
• Can engage both technology and business stakeholders.
• Builds strong relationships with Microsoft sellers and converts those relationships into opportunities.
• Knows when to qualify aggressively and when to walk away.
• Maintains strong pipeline and CRM discipline.
• Is comfortable navigating ambiguity while we rapidly scale our Azure business.
• Takes ownership from the first conversation through signed contract.
• Thinks beyond the initial transaction toward long-term customer value.

Why Join Comprinno

• Play a foundational role in building and scaling Comprinno's Microsoft Azure business.
• Sell transformation rather than a narrow technology product.
• Work across Cloud, Modernization, Security, Data, AI, Managed Services, and Platform Engineering.
• Build relationships with Microsoft and enterprise technology leaders.
• Work closely with experienced Cloud, AI, Presales, and Engineering teams.
• Participate directly in building a new growth engine within an established cloud technology company.
• Grow with an organization expanding from a strong AWS foundation into a broader multi-cloud and AI transformation company.

Assistant Sales Manager

The Assistant Sales Manager supports the Sales Manager in achieving sales targets, expanding the customer base, managing sales operations, and driving revenue growth. The role involves supervising the sales team, developing customer relationships, identifying new business opportunities, and ensuring effective execution of sales strategies.

Key Responsibilities:

• Assist in developing and implementing sales strategies and plans.
• Support the Sales Manager in achieving monthly and annual sales targets.
• Manage and motivate the sales team to improve performance.
• Generate leads and identify new business opportunities.
• Build and maintain strong customer relationships.
• Handle key customers and support account management activities.
• Monitor sales pipeline, leads, conversions, and follow-ups.
• Prepare sales reports, forecasts, and performance updates.
• Conduct market research and monitor competitor activities.
• Support pricing, negotiation, and deal-closing activities.
• Manage distributors, dealers, channel partners, or sales territories.
• Coordinate with marketing, operations, finance, and customer service teams.
• Track team performance and ensure timely achievement of targets.
• Provide sales training, coaching, and guidance to team members.
• Resolve customer issues and ensure high customer satisfaction.
• Ensure proper usage and updating of CRM and sales databases.

About Impact Analytics

Impact Analytics™ (Series D Funded) delivers AI-native SaaS solutions and consulting services that help companies maximize profitability and customer satisfaction through deeper data insights and predictive analytics. With a fully integrated, end-to-end platform for planning, forecasting, merchandising, pricing, and promotions, Impact Analytics empowers companies to make smarter decisions based on real-time insights rather than relying on last year’s inputs to forecast and plan this year’s business. Powered by over one million machine learning models, Impact Analytics has been leading AI innovation for a decade, setting new benchmarks in forecasting, planning, and operational excellence across the retail, grocery, manufacturing, and CPG sectors. In 2025, Impact Analytics is at the forefront of th eAgentic AI revolution, delivering autonomous solutions that enable businesses to adapt in real time, optimize operations, and drive profitability without manual intervention. Here’s a link to our website: www.impactanalytics.co.

The impact that you will be making

As a senior data scientist, you will help us discover the information hidden in vast amounts of data and help us make smarter decisions to deliver even better products. Primary focus will be in applying data mining techniques, performing statistical analysis, and building high quality prediction systems that can be integrated with our products.

What this role entail

● Understand and translate statistics and analytics to address client business problems.

● Apply Statistical forecasting algorithms to forecast client business needs for short term and long-term horizon.

● Explore Machine learning and Deep learning techniques to improve statistical Forecasting accuracy.

● Create business narrative by using storytelling and Visualization techniques and to present analytical insights to clients.

● Structure business problems and design solutions to meet client needs.

● Develop sophisticated analytical frameworks that add value to the client and result in new projects and revenue streams.

● Develop and implement analytical methodologies, processes, and technological solutions that integrate diverse information solutions and generate analytical insights.

What lands you in this role

● At least 3 years hands-on experience as a data scientist working on SQL, Python

● Must have exposure to developing predictive analytics and machine learning algorithms for business applications

● Strong forecasting and Deep Learning experience will be a plus

● Hands-on experience in relevant tools like SQL, Python, Tableau, etc.

● B Tech/ BE or equivalent degree in Data Science, Statistics, Computer Science, or similar

Some of our accolades include:

● Ranked as one of America's Fastest-Growing Companies by Financial Times for five consecutive years: 2020-2024.

● Ranked as one of America's Fastest-Growing Private Companies by Inc. 5000 for seven consecutive years: 2018-2024.

● Voted #1 by more than 300 retailers worldwide in the RIS Software Leaderboard 2024 report.

● Ranked #72 in America’s Most Innovative Companies list in 2023—by Fortune—alongside companies like Microsoft, Tesla, Apple, IBM, etc.

● Forged a strategic partnership with Google to equip retailers with cutting-edge generative AI tools.

● Recognized in multiple Gartner reports, including Market Guides and Hype Cycle, spanning assortments, merchandising, forecasting, algorithmic retailing, and Unified Price, Promotion, and Markdown Optimization Applications. Economic Times News about our funding can be accessed here.

Job Description – Data Scientist (Machine Learning & Forecasting)

About the Role

We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, Traditional Statistical Modelling, Forecasting, and Predictive Analytics. The ideal candidate will have hands-on experience building and deploying end-to-end ML solutions, working with large datasets, and translating business problems into scalable data science solutions.

The role requires a strong foundation in statistics, predictive modelling, feature engineering, model evaluation, and time-series forecasting, along with the ability to collaborate with cross-functional teams to deliver business impact.

Key Responsibilities

• Design, develop, and deploy Machine Learning models for business-critical use cases.
• Build and optimize traditional ML models such as:
• Linear Regression
• Logistic Regression
• Decision Trees
• Random Forest
• Gradient Boosting (XGBoost, LightGBM, CatBoost)
• Support Vector Machines
• Clustering Algorithms
• Develop forecasting solutions using:
• ARIMA / SARIMA
• Prophet
• Exponential Smoothing
• Time-Series Regression Models
• Perform exploratory data analysis (EDA), feature engineering, and data validation.
• Evaluate model performance using appropriate statistical and business metrics.
• Work with structured and semi-structured datasets from multiple sources.
• Collaborate with business stakeholders to understand requirements and translate them into analytical solutions.
• Build scalable data pipelines and support model deployment in production environments.
• Monitor model performance, identify data drift, and implement model retraining strategies.
• Present insights and recommendations to technical and non-technical stakeholders.

Required Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related quantitative field.
• 5+ years of hands-on experience in Data Science, Machine Learning, and Forecasting.

Technical Skills

   Machine Learning

• Strong understanding of supervised and unsupervised learning algorithms.
• Experience with ensemble methods and advanced ML techniques.
• Expertise in model selection, hyperparameter tuning, and performance optimization.

Forecasting & Statistics

• Strong understanding of:
• Time-Series Analysis
• Forecasting Techniques
• Statistical Inference
• Hypothesis Testing
• Probability Distributions
• A/B Testing

Programming

• Advanced proficiency in Python.
• Experience with:
• Pandas
• NumPy
• Scikit-learn
• Statsmodels
• XGBoost / LightGBM
• Prophet

Data & SQL

• Strong SQL skills with experience in complex queries and performance optimization.
• Experience working with large-scale datasets.

Visualization

• Experience with Power BI, Tableau, Matplotlib, Seaborn, or Plotly.
• Cloud & MLOps (Preferred)
• Exposure to AWS, Azure, or GCP.
• Understanding of Docker, Kubernetes, CI/CD, and ML model deployment practices.

Key Competencies

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management abilities.
• Ability to work independently in a fast-paced environment.
• Strong business acumen and data-driven decision-making mindset. 

Machine Learning Engineer / AI Engineer

2 to 10 Years Experience

What if your models didn't just forecast demand — they autonomously acted on it?

We're building the next generation of supply chain intelligence, where AI agents don't just predict — they reason, decide, and adapt. If you're the kind of engineer who gets excited about turning a forecast into an autonomous decision engine, this role is for you.

Be Part of Something Bigger

At our core, we own the challenge and drive the future — taking full responsibility for delivering smart, sustainable solutions that optimize supply chains. We believe knowledge fuels confidence, fostering continuous learning, innovation, and expertise to push boundaries with clarity and purpose.

With a commitment to opportunities for all and growth for everyone, we create pathways for success, empowering individuals to thrive. Our strength lies in being stronger, smarter, together — harnessing diverse perspectives and collaboration to drive bold ideas. Above all, we focus on impact that matters and results that last, building intelligent, sustainable solutions that create long-term value for businesses and the world.

What You'll Build

You'll architect intelligent systems that sense demand shifts in real time and recommend actions before a human even asks. Specifically, you will work across:

•      Agentic AI pipelines that go beyond prediction — systems that reason, decide, and adapt autonomously

•      Advanced demand forecasting and sensing models using attribute-based and cohort-based approaches

•      Signal integration frameworks that fuse external data and real-time market inputs

•      Feature engineering at scale — lag structures, rolling aggregations, and derived features

•      Model performance frameworks tied directly to measurable business outcomes

•      Translating complex model insights into clear, actionable language for clients and leadership

Who You Are

You bring a strong foundation in machine learning and a genuine curiosity about where AI is heading. The ideal candidate has:

•      2–10 years of hands-on experience in ML, AI, or Data Science with proven model-building track record

•      Python fluency — pandas, scikit-learn, XGBoost, LightGBM are second nature to you

•      Deep understanding of time series forecasting and experience with large-scale transactional datasets

•      Ability to connect model outputs to real business impact and articulate the 'so what' clearly

•      Genuine curiosity about the power of AI and openness to emerging tools and paradigms — including agentic and generative AI

Bonus Points

•      Experience in retail, supply chain, or inventory planning domains

•      Exposure to hierarchical forecasting, new product forecasting, or ensemble methods

•      Hands-on work with LLM-based agents or orchestration frameworks

Why This Role Is Different

Your models won't sit in a notebook — they'll drive decisions for real companies managing real inventory and real revenue.

•      Work at the cutting edge of agentic AI in supply chain, a space being reinvented right now

•      See your models directly influence supply chain decisions for enterprise brands, retailers, and grocers

•      Collaborate with a team of domain experts, data scientists, and product leaders who obsess over outcomes

•      Invest your curiosity in shaping how AI transforms an entire industry from the ground up

Key Performance Indicators

•      Model accuracy, reliability, and real-world forecast performance

•      Speed and quality of model deployment to production pipelines

•      Business impact of AI-driven recommendations — measured in inventory efficiency and revenue outcomes

•      Cross-functional collaboration effectiveness with product, engineering, and client teams

Hi,

Greetings from Ampera!

we are looking for a Data Scientist with strong Python & Forecasting experience.

Title                               : Data Scientist – Python & Forecasting

Experience                   : 4 to 7 Yrs

Location                       : Chennai/Bengaluru

Type of hire                  : PWD and Non PWD

Employment Type     : Full Time

Notice Period             : Immediate Joiner

Working hours           : 09:00 a.m. to 06:00 p.m.

Workdays                   : Mon - Fri

Job Description:

We are looking for an experienced Data Scientist with strong expertise in Python programming and forecasting techniques. The ideal candidate should have hands-on experience building predictive and time-series forecasting models, working with large datasets, and deploying scalable solutions in production environments.

Key Responsibilities

• Develop and implement forecasting models (time-series and machine learning based).
• Perform exploratory data analysis (EDA), feature engineering, and model validation.
• Build, test, and optimize predictive models for business use cases such as demand forecasting, revenue prediction, trend analysis, etc.
• Design, train, validate, and optimize machine learning models for real-world business use cases.
• Apply appropriate ML algorithms based on business problems and data characteristics
• Write clean, modular, and production-ready Python code.
• Work extensively with Python Packages & libraries for data processing and modelling.
• Collaborate with Data Engineers and stakeholders to deploy models into production.
• Monitor model performance and improve accuracy through continuous tuning.
• Document methodologies, assumptions, and results clearly for business teams.

Technical Skills Required:

Programming

• Strong proficiency in Python
• Experience with Pandas, NumPy, Scikit-learn

Forecasting & Modelling

• Hands-on experience in Time Series Forecasting (ARIMA, SARIMA, Prophet, etc.)
• Experience with ML-based forecasting models (XGBoost, LightGBM, Random Forest, etc.)
• Understanding of seasonality, trend decomposition, and statistical modeling

Data & Deployment

• Experience handling structured and large datasets
• SQL proficiency
• Exposure to model deployment (API-based deployment preferred)
• Knowledge of MLOps concepts is an added advantage

Tools (Preferred)

• TensorFlow / PyTorch (optional)
• Airflow / MLflow
• Cloud platforms (AWS / Azure / GCP)

Educational Qualification

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or related field.

Key Competencies

• Strong analytical and problem-solving skills
• Ability to communicate insights to technical and non-technical stakeholders
• Experience working in agile or fast-paced environments

Accessibility & Inclusion Statement

We are committed to creating an inclusive environment for all employees, including persons with disabilities. Reasonable accommodations will be provided upon request.

Equal Opportunity Employer (EOE) Statement

Ampera Technologies is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Required Skills: Techno-Commercial Sales Expertise, B2B / Institutional Sales & Business Development, Technical Knowledge of Textiles, Negotiation & Relationship Management, Market Intelligence & Strategic Selling

Criteria:

It's a sales profile so need a strong sales person from textile sector who can do the B2B / OEM / Institutional sales 

• Experience: 5 to 20 years in Technical Textiles or allied industrial textile sectors (Agri, Geo, Packaging, Automotive)
• Proven experience in B2B / OEM / Institutional Sales within industrial or technical textiles
• Candidate should have experience in selling Fabric and Technical Textiles.
• Strong techno-commercial acumen – ability to link product performance, costing, and customer application
• Hands-on experience in pricing, proposals, negotiations, and margin management
• Exposure to product development coordination with R&D, Production, and Quality teams
• Excellent communication, negotiation, and relationship management skills
• Preferred experience in international business development (mandatory for export roles)
• Strong analytical, reporting, and forecasting abilities
• Willingness to travel within India and overseas as per business requirements.

Open Position:

Techno-Commercial Sales (Manager / Sr. Manager / AGM / GM)

Description

What You’ll Do:

• Lead B2B and institutional sales in your assigned technical textile vertical.

• Identify and onboard new customers, distributors, and OEMs in both domestic and export markets.

• Offer techno-commercial solutions tailored to customer applications and performance requirements.

• Work closely with R&D, Production, and Quality teams for trials, samples, and custom developments.

• Manage pricing, proposals, and negotiations, backed by a strong understanding of product costing, margins, and profitability.

• Track and report market trends, competitor movements, and emerging business opportunities.

• Deliver on sales and margin targets, while building long-term customer relationships.

Who You Are:

• Qualification: B.Tech / Diploma (Textiles, Polymers, Mechanical) or MBA (Marketing).

• Experience: 5–20 years in Technical Textiles or allied industrial textile sectors – Agri, Geo, Packaging, or Automotive.

• Strong techno-commercial mindset, with the ability to connect product performance and costing to customer needs.

• Proven background in B2B / OEM / institutional sales.

• Excellent communication, negotiation, and relationship management skills.

• For export roles, international business development experience is essential.

Preferred Background:

We’re looking for people who have worked with established technical textile or industrial fabric manufacturers, particularly in areas such as:

• Agri Textiles: Shade nets, crop covers, pond liners, etc.

• Geo Textiles: Woven / nonwoven fabrics, reinforcement, filtration, erosion control.

• Packaging Textiles: PP/HDPE woven, FIBC, industrial sacks.

• Automotive or Industrial Textiles: Roof liners, filtration media, composites, or performance fabrics.

A Financial Research Analyst is responsible for gathering, analyzing, and interpreting financial data to support investment decisions, business strategies, or financial forecasting. Their primary role is to provide insights and recommendations based on their research to help guide the organization or clients in making informed financial decisions.

Key Responsibilities:

Data Collection & Analysis:

• Gather financial data from various sources (e.g., financial statements, market reports, industry trends, etc.).
• Analyze financial information, including profit and loss statements, balance sheets, and cash flow reports.

Market and Industry Research:

• Research industry trends, economic conditions, and market conditions to identify investment opportunities or risks.
• Track competitor performance and benchmarking.

Financial Modeling and Forecasting:

• Build and maintain financial models to project future performance, such as forecasting revenue and expenses.
• Use quantitative tools to evaluate investment options and potential financial outcomes.

Report Creation:

• Prepare detailed reports summarizing findings, analyses, and recommendations for internal stakeholders or clients.
• Present research findings to management, clients, or investors in a clear and concise manner.

Investment Recommendations:

• Provide recommendations for investment opportunities, such as stocks, bonds, or alternative investments.
• Assist with the evaluation of portfolios and asset management strategies.

Risk Assessment:

• Assess financial risks related to investments, projects, or business decisions.
• Recommend risk management strategies based on data analysis.

Collaboration & Communication:

• Work closely with other teams, such as investment managers, accountants, or business strategists, to align research with broader business objectives.
• Communicate findings and insights clearly to both financial and non-financial stakeholders.

Key Responsibilities :

- Ensuring monthly book closure, revenue recognition & accrual of proper costs in all categories to be in line with the internal guidelines and the statutory requirements

- Preparation of MIS reports, schedules, reports & MTM change analysis.

- Validating monthly revenues, analytical checks on system reports

- Ensure compliance of all statutory audits, internal audits & ICFR related requirements within timelines.

- Drive automation for various reports & activities.

- Collaborate with internal stakeholders for reporting requirements

- Work with the team for preparation of the monthly closure & Quarterly Audit plans

Job Requirements :

- CA with good academic records

- Systematically process, measure and verify financial and accounting information

- Analyze financial details and do value addition to business - Strong Bias for action, problem solving and ownership Full Time Employee Benefits (Not applicable for Intern or Contract Roles)

• Insurance Benefits - Medical Insurance, Critical Illness Insurance, Accidental Insurance, Life Insurance

• Wellness Program - Employee Assistance Program, Onsite Medical Center, Emergency Support System

• Parental Support - Maternity Benefit, Paternity Benefit Program, Adoption Assistance Program, Day-care Support Program

• Mobility Benefits - Relocation benefits, Transfer Support Policy, Travel Policy

• Retirement Benefits - Employee PF Contribution, Flexible PF Contribution, Gratuity, NPS, Leave Encashment

• Other Benefits - Higher Education Assistance, Car Lease, Mobile & Broadband Reimbursements, Salary Advance Policy

Will be incharge for Digital Marketing, Web development , Business consulting to startups and sick unit Domain and accountable for Profit Generation .

Develop goals and objectives that tend to growth and prosperity

Design and implement business plans and strategies to promote the attainment of goals

Ensure that the company has the adequate and suitable resources to complete its activities (e.g. people, material, equipment etc.)

Organize and coordinate operations in ways that ensure maximum productivity and Profitable.

Supervise the work of employees and provide feedback and counsel to improve efficiency and effectiveness

Maintain relationships with partners/vendors/suppliers

Gather, analyze and interpret external and internal data and write reports

Assess overall department  performance against objectives

Represent the company in events, conferences etc.

Ensure adherence to legal rules and guidelines

Coordinate with Technical Team to deliver better service.

Will be incharge for Marketing , Sales, Managing Team , Service , Business Forcasting  and Planing.

KRA.

Month on Month Profit Generation by effectively Running the Business unit.

Always should Exceed the Customers Expectation

Company Profile:

The company is World's No1 Global management consulting firm.

Job Title – Data Scientist (Forecasting)

Anicca Data is seeking a Data Scientist (Forecasting) who is motivated to apply his/her/their skill set to solve complex and challenging problems. The focus of the role will center around applying deep learning models to real-world applications.  The candidate should have experience in training, testing deep learning architectures.  This candidate is expected to work on existing codebases or write an optimized codebase at Anicca Data. The ideal addition to our team is self-motivated, highly organized, and a team player who thrives in a fast-paced environment with the ability to learn quickly and work independently.

Job Location: Remote (for time being) and Bangalore, India (post-COVID crisis)

• At least 3+ years of experience in a Data Scientist role
• Bachelor's/Master’s degree in Computer Science, Engineering, Statistics, Mathematics, or similar quantitative discipline. D. will add merit to the application process
• Experience with large data sets, big data, and analytics
• Exposure to statistical modeling, forecasting, and machine learning. Deep theoretical and practical knowledge of deep learning, machine learning, statistics, probability, time series forecasting
• Training Machine Learning (ML) algorithms in areas of forecasting and prediction
• Experience in developing and deploying machine learning solutions in a cloud environment (AWS, Azure, Google Cloud) for production systems
• Research and enhance existing in-house, open-source models, integrate innovative techniques, or create new algorithms to solve complex business problems
• Experience in translating business needs into problem statements, prototypes, and minimum viable products
• Experience managing complex projects including scoping, requirements gathering, resource estimations, sprint planning, and management of internal and external communication and resources
• Write C++ and Python code along with TensorFlow, PyTorch to build and enhance the platform that is used for training ML models

Preferred Experience

• Worked on forecasting projects – both classical and ML models
• Experience with training time series forecasting methods like Moving Average (MA) and Autoregressive Integrated Moving Average (ARIMA) with Neural Networks (NN) models as Feed-forward NN and Nonlinear Autoregressive
• Strong background in forecasting accuracy drivers
• Experience in Advanced Analytics techniques such as regression, classification, and clustering
• Ability to explain complex topics in simple terms, ability to explain use cases and tell stories