18+ Predictive modelling Jobs in India

About Moative

Moative, an Applied AI Services company, designs AI roadmaps, builds co-pilots and predictive AI solutions for companies in energy, utilities, packaging, commerce, and other primary industries. Through Moative Labs, we aspire to build micro-products and launch AI startups in vertical markets.

Our Past: We have built and sold two companies, one of which was an AI company. Our founders and leaders are Math PhDs, Ivy League University Alumni, Ex-Googlers, and successful entrepreneurs. 

Role

We seek skilled and experienced data science/machine learning professionals with a strong background in at least one of mathematics, financial engineering, and electrical engineering, to join our Energy & Utilities team. If you are interested in artificial intelligence, excited about solving real business problems in the energy and utilities industry, and keen to contribute to impactful projects, this role is for you!

Work you’ll do

As a data scientist in the energy and utilities industry, you will perform quantitative analysis and build mathematical models to forecast energy demand, supply and strategies of efficient load balancing. You will work on models for short term and long term pricing, improving operational efficiency, reducing costs, and ensuring reliable power supply. You’ll work closely with cross-functional teams to deploy these models in solutions that provide insights/ solutions to real-world business problems. You will also be involved in conducting experiments, building POCs and prototypes.

Responsibilities

• Develop and implement quantitative models for load forecasting, energy production and distribution optimization.
• Analyze historical data to identify and predict extreme events, and measure impact of extreme events. Enhance existing pricing and risk management frameworks.
• Develop and implement quantitative models for energy pricing and risk management. Monitor market conditions and adjust models as needed to ensure accuracy and effectiveness.
• Collaborate with engineering and operations teams to provide quantitative support for energy projects. Enhance existing energy management systems and develop new strategies for energy conservation.
• Maintain and improve quantitative tools and software used in energy management.
• Support end-to-end ML/ AI model lifecycle - from data preparation, data analysis and feature engineering to model development, validation and deployment
• Collaborate with domain experts, engineers, and stakeholders in translating business problems into data-driven solutions
• Document methodologies and results, present findings and communicate insights to non-technical audiences

Skills & Requirements

• Strong background in mathematics, econometrics, electrical engineering, or a related eld.
• Experience data analysis, and quantitative modeling using programming languages such as Python or R.
• Excellent analytical and problem-solving skills.
• Strong understanding and experience with data analysis, statistical and mathematical concepts and ML algorithms
• Proficiency in Python and familiarity with basic Python libraries for data analysis and ML algorithms (such as NumPy, Pandas, ScikitLearn, NLTK).
• Strong communication skills
• Strong collaboration skills, ability to work with engineering and operations teams.
• A continuous learning attitude and a problem solving mind-set

Good to have -

• Knowledge of energy markets, regulations, and utility operation.
• Working knowledge of cloud platforms (e.g., AWS, Azure, GCP).
• Broad understanding of data structures and data engineering.

Working at Moative

Moative is a young company, but we believe strongly in thinking long-term, while acting with urgency. Our ethos is rooted in innovation, efficiency and high-quality outcomes. We believe the future of work is AI-augmented and boundary less. Here are some of our guiding principles:

• Think in decades. Act in hours. As an independent company, our moat is time. While our decisions are for the long-term horizon, our execution will be fast – measured in hours and days, not weeks and months.
• Own the canvas. Throw yourself in to build, x or improve – anything that isn’t done right, irrespective of who did it. Be selfish about improving across the organization – because once the rot sets in, we waste years in surgery and recovery.
• Use data or don’t use data. Use data where you ought to but not as a ‘cover-my-back’ political tool. Be capable of making decisions with partial or limited data. Get better at intuition and pattern-matching. Whichever way you go, be mostly right about it.
• Avoid work about work. Process creeps on purpose, unless we constantly question it. We are deliberate about committing to rituals that take time away from the actual work. We truly believe that a meeting that could be an email, should be an email and you don’t need a person with the highest title to say that loud.
• High revenue per person. We work backwards from this metric. Our default is to automate instead of hiring. We multi-skill our people to own more outcomes than hiring someone who has less to do. We don’t like squatting and hoarding that comes in the form of hiring for growth. High revenue per person comes from high quality work from everyone. We demand it.

If this role and our work is of interest to you, please apply here. We encourage you to apply even if you believe you do not meet all the requirements listed above.

That said, you should demonstrate that you are in the 90th percentile or above. This may mean that you have studied in top-notch institutions, won competitions that are intellectually demanding, built something of your own, or rated as an outstanding performer by your current or previous employers.

The position is based out of Chennai. Our work currently involves significant in-person collaboration and we expect you to work out of our offices in Chennai.

Job Title:- Head of Analytics

Job Location:- Bangalore - On - site

About Qrata:

Qrata matches top talent with global career opportunities from the world’s leading digital companies including some of the world’s fastest growing start-ups using qrata’s talent marketplaces. To sign-up please visit Qrata Talent Sign-Up

We are currently scouting for Head of Analytics

Our Client Story:

Founded by a team of seasoned bankers with over 120 years of collective experience in banking, financial services and cards, encompassing strategy, operation, marketing, risk & technology, both in India and internationally.

We offer credit card processing Solution that can help you in effectively managing your credit card portfolio end-to-end. These solution are customized to meet the unique strategic, operational and compliance requirements of each bank.

1. Card Programs built for Everyone Limit assignment based on customer risk assessment & credit profiles including secured cards

2. Cards that can be used Everywhere. Through POS machines, UPI, E-Commerce websites

3. A Card for Everything Enable customer purchases, both large and small

4. Customized Card configurations Restrict usage based on merchant codes, location, amount limits etc

5. End-to-End Support We undertake the complete customer life cycle management right from KYC checks, onboarding, risk profiling, fraud control, billing and collections

6. Rewards Program Management We will manage the entire cards reward and customer loyalty programs for you

What you will do:

We are seeking an experienced individual for the role of Head of Analytics. As the Head of Analytics, you will be responsible for driving data-driven decision-making, implementing advanced analytics strategies, and providing valuable insights to optimize our credit card business operations, sales and marketing, risk management & customer experience. Your expertise in statistical analysis, predictive modelling, and data visualization will be instrumental in driving growth and enhancing the overall performance of our credit card business

Qualification:

• Bachelor's or master’s degree in Technology, Mathematics, Statistics, Economics, Computer Science, or a related field
• Proven experience (7+ years) in leading analytics teams in the credit card industry
• Strong expertise in statistical analysis, predictive modelling, data mining, and segmentation techniques
• Proficiency in data manipulation and analysis using programming languages such as Python, R, or SQL
• Experience with analytics tools such as SAS, SPSS, or Tableau
• Excellent leadership and team management skills, with a track record of building and developing high-performing teams
• Strong knowledge of credit card business and understanding of credit card industry dynamics, including risk management, marketing, and customer lifecycle
• Exceptional communication and presentation skills, with the ability to effectively communicate complex information to a varied audience

What you can expect:

1. Develop and implement Analytics Strategy:

o Define the analytics roadmap for the credit card business, aligning it with overall business objectives

o Identify key performance indicators (KPIs) and metrics to track the performance of the credit card business

o Collaborate with senior management and cross-functional teams to prioritize and execute analytics initiatives

2. Lead Data Analysis and Insights:

o Conduct in-depth analysis of credit card data, customer behaviour, and market trends to identify opportunities for business growth and risk mitigation

o Develop predictive models and algorithms to assess credit risk, customer segmentation, acquisition, retention, and upsell opportunities

o Generate actionable insights and recommendations based on data analysis to optimize credit card product offerings, pricing, and marketing strategies

o Regularly present findings and recommendations to senior leadership, using data visualization techniques to effectively communicate complex information

3. Drive Data Governance and Quality:

o Oversee data governance initiatives, ensuring data accuracy, consistency, and integrity across relevant systems and platforms

o Collaborate with IT teams to optimize data collection, integration, and storage processes to support advanced analytics capabilities

o Establish and enforce data privacy and security protocols to comply with regulatory requirements

4. Team Leadership and Collaboration:

o Build and manage a high-performing analytics team, fostering a culture of innovation, collaboration, and continuous learning

o Provide guidance and mentorship to the team, promoting professional growth and development

o Collaborate with stakeholders across departments, including Marketing, Risk Management, and Finance, to align analytics initiatives with business objectives

5. Stay Updated on Industry Trends:

o Keep abreast of emerging trends, techniques, and technologies in analytics, credit card business, and the financial industry

o Leverage industry best practices to drive innovation and continuous improvement in analytics methodologies and tools

For more Opportunities Visit: Qrata Opportunities.

Role: Head of Analytics

Location: Bangalore (Full time)

ABOUT QRATA: 

Qrata matches top talent with global career opportunities from the world’s leading digital companies including some of the world’s fastest growing startups using Qrata’s talent marketplaces. To sign-up, please visit Qrata Talent Sign-Up 

ABOUT THE COMPANY WE ARE HIRING FOR: 

Our client is offering credit card solutions for banks and financial institutions. It provides services like credit card design and onboarding, credit card authorization, payment processing, collections and dispute resolutions, credit card fraud detection, and more. They serve in the B2B space in the FinTech market segments.

POSITION OVERVIEW 

We are seeking an experienced individual for the role of Head of Analytics. As the Head of Analytics, you will be responsible for driving data-driven decision-making, implementing advanced analytics strategies, and providing valuable insights to optimize our credit card business operations, sales and marketing, risk management & customer experience. Your expertise in statistical analysis, predictive modeling, and data visualization will be instrumental in driving growth and enhancing the overall performance of our credit card business.

Responsibilities:

1. Develop and implement Analytics Strategy:

o Define the analytics roadmap for the credit card business, aligning it with overall

business objectives.

o Identify key performance indicators (KPIs) and metrics to track the performance

of the credit card business.

o Collaborate with senior management and cross-functional teams to prioritize and

execute analytics initiatives. 2. Lead Data Analysis and Insights:

o Conduct in-depth analysis of credit card data, customer behavior, and market trends to identify opportunities for business growth and risk mitigation.

o Develop predictive models and algorithms to assess credit risk, customer segmentation, acquisition, retention, and upsell opportunities.

o Generate actionable insights and recommendations based on data analysis to optimize credit card product offerings, pricing, and marketing strategies.

o Regularly present findings and recommendations to senior leadership, using data visualization techniques to effectively communicate complex information.

3. Drive Data Governance and Quality:

o Oversee data governance initiatives, ensuring data accuracy, consistency, and

integrity across relevant systems and platforms.

o Collaborate with IT teams to optimize data collection, integration, and storage

processes to support advanced analytics capabilities.

o Establish and enforce data privacy and security protocols to comply with

regulatory requirements.

4. Team Leadership and Collaboration:

o Build and manage a high-performing analytics team, fostering a culture of innovation, collaboration, and continuous learning.

o Provide guidance and mentorship to the team, promoting professional growth and development.

o Collaborate with stakeholders across departments, including Marketing, Risk Management, and Finance, to align analytics initiatives with business objectives.

5. Stay Updated on Industry Trends:

o Keep abreast of emerging trends, techniques, and technologies in analytics, credit

card business, and the financial industry.

o Leverage industry best practices to drive innovation and continuous improvement

in analytics methodologies and tools.

Qualifications:

Bachelor's or master’s degree in Technology, Mathematics, Statistics, Economics, Computer Science, or a related field.

Proven experience (7+ years) in leading analytics teams in the credit card industry.

Strong expertise in statistical analysis, predictive modelling, data mining, and segmentation techniques.

Proficiency in data manipulation and analysis using programming languages such as Python, R, or SQL.

Experience with analytics tools such as SAS, SPSS, or Tableau.

Excellent leadership and team management skills, with a track record of building and developing high-performing teams.

Strong knowledge of credit card business and understanding of credit card industry dynamics, including risk management, marketing, and customer lifecycle.

Exceptional communication and presentation skills, with the ability to effectively communicate complex information to a varied audience. 

At Livello we building machine-learning-based demand forecasting tools as well as computer-vision-based multi-camera product recognition solutions that detects people and products to track the inserted/removed items on shelves based on the hand movement of users. We are building models to determine real-time inventory levels, user behaviour as well as predicting how much of each product needs to be reordered so that the right products are delivered to the right locations at the right time, to fulfil customer demand.

Responsibilities

• Lead the CV and DS Team
• Work in the area of Computer Vision and Machine Learning, with focus on product (primarily food) and people recognition (position, movement, age, gender, DSGVO compliant).
• Your work will include formulation and development of a Machine Learning models to solve the underlying problem.
• You help build our smart supply chain system, keep up to date with the latest algorithmic improvements in forecasting and predictive areas, challenge the status quo
• Statistical data modelling and machine learning research.
• Conceptualize, implement and evaluate algorithmic solutions for supply forecasting, inventory optimization, predicting sales, and automating business processes
• Conduct applied research to model complex dependencies, statistical inference and predictive modelling
• Technological conception, design and implementation of new features
• Quality assurance of the software through planning, creation and execution of tests
• Work with a cross-functional team to define, build, test, and deploy applications

Requirements:

• Master/PHD in Mathematics, Statistics, Engineering, Econometrics, Computer Science or any related fields.
• 3-4 years of experience with computer vision and data science.
• Relevant Data Science experience, deep technical background in applied data science (machine learning algorithms, statistical analysis, predictive modelling, forecasting, Bayesian methods, optimization techniques).
• Experience building production-quality and well-engineered Computer Vision and Data Science products.
• Experience in image processing, algorithms and neural networks.
• Knowledge of the tools, libraries and cloud services for Data Science. Ideally Google Cloud Platform
• Solid Python engineering skills and experience with Python, Tensorflow, Docker
• Cooperative and independent work, analytical mindset, and willingness to take responsibility
• Fluency in English, both written and spoken.

Responsibilities

This role requires a person to support business charters & accompanying products by aligning with the Analytics

Manager’s vision, understanding tactical requirements and helping in successful execution. Split would be approx.

70% management + 30% individual contributor. Responsibilities include

Project Management

- Understand business needs and objectives.

- Refine use cases and plan iterations and deliverables - able to pivot as required.

- Estimate efforts and conduct regular task updates to ensure timeline adherence.

- Set and manage stakeholder expectations as required

Quality Execution

- Help BA and SBA resources with requirement gathering and final presentations.

- Resolve blockers regarding technical challenges and decision-making.

- Check final deliverables for correctness and review codes, along with Manager.

KPIs and metrics

- Orchestrate metrics building, maintenance, and performance monitoring.

- Owns and manages data models, data sources, and data definition repo.

- Makes low-level design choices during execution.

Team Nurturing

- Help Analytics Manager during regular one-on-ones + check-ins + recruitment.

- Provide technical guidance whenever required.

- Improve benchmarking and decision-making skills at execution-level.

- Train and get new resources up-to-speed.

- Knowledge building (methodologies) to better position the team for complex problems.

Communication

- Upstream to document and discuss execution challenges, process inefficiencies, and feedback loops.

- Downstream and parallel for context-building, mentoring, stakeholder management.

Analytics Stack

- Analytics : Python / R + SQL + Excel / PPT, Colab notebooks

- Database : PostgreSQL, Amazon Redshift, DynamoDB, Aerospike

- Warehouse : Amazon Redshift

- ETL : Lots of Python + custom-made

- Business Intelligence / Visualization : Metabase + Python/R libraries (location data)

- Deployment pipeline : Docker, Git, Jenkins, AWS Lambda

• Work closely with your business to identify issues and use data to propose solutions for effective decision making
• Build algorithms and design experiments to merge, manage, interrogate and extract data to supply tailored reports to colleagues, customers or the wider organisation.
• Creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc
• Querying databases and using statistical computer languages: R, Python, SLQ, etc.
• Visualizing/presenting data through various Dashboards for Data Analysis, Using Python Dash, Flask etc.
• Test data mining models to select the most appropriate ones for use on a project
• Work in a POSIX/UNIX environment to run/deploy applications
• Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
• Develop custom data models and algorithms to apply to data sets.
• Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
• Assess the effectiveness of data sources and data-gathering techniques and improve data collection methods
• Horizon scan to stay up to date with the latest technology, techniques and methods
• Coordinate with different functional teams to implement models and monitor outcomes.
• Stay curious and enthusiastic about using algorithms to solve problems and enthuse others to see the benefit of your work.

• Able to create algorithms to extract information from large data sets
• Strong knowledge of Python, R, Java or another scripting/statistical languages to automate data retrieval, manipulation and analysis.
• Experience with extracting and aggregating data from large data sets using SQL or other tools
• Strong understanding of various NLP, and NLU techniques like Named Entity Recognition, Summarization, Topic Modeling, Text Classification, Lemmatization and Stemming.
• Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, etc.
• Experience with Python libraries such as Pandas, NumPy, SciPy, Scikit-Learn
• Experience with Jupyter / Pandas / Numpy to manipulate and analyse data
• Knowledge of Machine Learning techniques and their respective pros and cons
• Strong Knowledge of various Data Science Visualization Tools like Tableau, PowerBI, D3, Plotly, etc.
• Experience using web services: Redshift, AWS, S3, Spark, DigitalOcean, etc.
• Proficiency in using query languages, such as SQL, Spark DataFrame API, etc.
• Hands-on experience in HTML, CSS, Bootstrap, JavaScript, AJAX, jQuery and Prototyping.
• Hands-on experience on C#, Javascript, .Net
• Experience in understanding and analyzing data using statistical software (e.g., Python, R, KDB+ and other relevant libraries)
• Experienced in building applications that meet enterprise needs – secure, scalable, loosely coupled design
• Strong knowledge of computer science, algorithms, and design patterns
• Strong oral and written communication, and other soft skills critical to collaborating and engage with teams

What you need to have:

We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.

Skills:

- 5+ years deploying Machine Learning pipelines in large enterprise production systems.

- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.

Roles and Responsibilities:

Deploying ML models into production, and scaling them to serve millions of customers.

Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.

Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.

Provide software design and programming support to projects.

 Qualifications & Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.

Ganit has flipped the data science value chain as we do not start with a technique but for us, consumption comes first. With this philosophy, we have successfully scaled from being a small start-up to a 200 resource company with clients in the US, Singapore, Africa, UAE, and India. 

We are looking for experienced data enthusiasts who can make the data talk to them. 

You will: 

• Understand business problems and translate business requirements into technical requirements. 
• Conduct complex data analysis to ensure data quality & reliability i.e., make the data talk by extracting, preparing, and transforming it. 
• Identify, develop and implement statistical techniques and algorithms to address business challenges and add value to the organization. 
• Gather requirements and communicate findings in the form of a meaningful story with the stakeholders  
• Build & implement data models using predictive modelling techniques. Interact with clients and provide support for queries and delivery adoption. 
• Lead and mentor data analysts. 

We are looking for someone who has: 

• Apart from your love for data and ability to code even while sleeping you would need the following. 
• Minimum of 02 years of experience in designing and delivery of data science solutions. 
• You should have successful projects of retail/BFSI/FMCG/Manufacturing/QSR in your kitty to show-off. 
• Deep understanding of various statistical techniques, mathematical models, and algorithms to start the conversation with the data in hand. 
• Ability to choose the right model for the data and translate that into a code using R, Python, VBA, SQL, etc. 
• Bachelors/Masters degree in Engineering/Technology or MBA from Tier-1 B School or MSc. in Statistics or Mathematics 

Skillset Required:

• Regression
• Classification
• Predictive Modelling
• Prescriptive Modelling
• Python
• R
• Descriptive Modelling
• Time Series
• Clustering
•  

What is in it for you: 

• Be a part of building the biggest brand in Data science. 
• An opportunity to be a part of a young and energetic team with a strong pedigree. 
• Work on awesome projects across industries and learn from the best in the industry, while growing at a hyper rate. 

Please Note:  

At Ganit, we are looking for people who love problem solving. You are encouraged to apply even if your experience does not precisely match the job description above. Your passion and skills will stand out and set you apart—especially if your career has taken some extraordinary twists and turns over the years. We welcome diverse perspectives, people who think rigorously and are not afraid to challenge assumptions in a problem. Join us and punch above your weight! 

Ganit is an equal opportunity employer and is committed to providing a work environment that is free from harassment and discrimination. 

All recruitment, selection procedures and decisions will reflect Ganit’s commitment to providing equal opportunity. All potential candidates will be assessed according to their skills, knowledge, qualifications, and capabilities. No regard will be given to factors such as age, gender, marital status, race, religion, physical impairment, or political opinions. 

Ganit Inc. is the fastest growing Data Science & AI company in Chennai.

Founded in 2017, by 3 industry experts who are alumnus of IITs/SPJIMR with each of them having 17+ years of experience in the field of analytics.

We are in the business of maximising Decision Making Power (DMP) for companies by providing solutions at the intersection of hypothesis based analytics, discovery based AI and IoT. Our solutions are a combination of customised services and functional product suite.

We primarily operate as a US-based start-up and have clients across US, Asia-Pacific, Middle-East and have offices in USA - New Jersey & India - Chennai.

Started with 3 people, the company is fast growing with 100+ employees

1. What do we expect from you

- Should posses minimum 2 years of experience of data analytics model development and deployment

- Skills relating to core Statistics & Mathematics.

- Huge interest in handling numbers

- Ability to understand all domains in businesses across various sectors

- Natural passion towards numbers, business, coding, visualisation

2. Necessary skill set:

- Proficient in R/Python, Advanced Excel, SQL

- Should have worked with Retail/FMCG/CPG projects solving analytical problems in Sales/Marketing/Supply Chain functions

- Very good understanding of algorithms, mathematical models, statistical techniques, data mining, like Regression models, Clustering/ Segmentation, time series forecasting, Decision trees/Random forest, etc.

- Ability to choose the right model for the right data and translate that into code in R, Python, VBA (Proven capabilities)

- Should have handled large datasets and with through understanding of SQL

- Ability to handle a team of Data Analysts

3. Good to have skill set:

- Microsoft PowerBI / Tableau / Qlik View / Spotfire

4. Job Responsibilities:

- Translate business requirements into technical requirements

- Data extraction, preparation and transformation

- Identify, develop and implement statistical techniques and algorithms that address business challenges and adds value to the organisation

- Create and implement data models

- Interact with clients for queries and delivery adoption

5. Screening Methodology

- Problem Solving round (Telephonic Conversation)

- Technical discussion round (Telephonic Conversation)

- Final fitment discussion (Video Round

Responsibilities: 

• Identify complex business problems and work towards building analytical solutions in-order to create large business impact.
• Demonstrate leadership through innovation in software and data products from ideation/conception through design, development and ongoing enhancement, leveraging user research techniques, traditional data tools, and techniques from the data science toolkit such as predictive modelling, NLP, statistical analysis, vector space modelling, machine learning etc.
• Collaborate and ideate with cross-functional teams to identify strategic questions for the business that can be solved and champion the effectiveness of utilizing data, analytics, and insights to shape business.
• Contribute to company growth efforts, increasing revenue and supporting other key business outcomes using analytics techniques.
• Focus on driving operational efficiencies by use of data and analytics to impact cost and employee efficiency.
• Baseline current analytics capability, ensure optimum utilization and continued advancement to stay abridge with industry developments.
• Establish self as a strategic partner with stakeholders, focused on full innovation system and fully supportive of initiatives from early stages to activation.
• Review stakeholder objectives and team's recommendations to ensure alignment and understanding.
• Drive analytics thought leadership and effectively contributes towards transformational initiatives.
• Ensure accuracy of data and deliverables of reporting employees with comprehensive policies and processes.

The person holding this position is responsible for leading the solution development and implementing advanced analytical approaches across a variety of industries in the supply chain domain.

At this position you act as an interface between the delivery team and the supply chain team, effectively understanding the client business and supply chain.

Candidates will be expected to lead projects across several areas such as

• Demand forecasting
• Inventory management
• Simulation & Mathematical optimization models.
• Procurement analytics
• Distribution/Logistics planning
• Network planning and optimization

Qualification and Experience

• 4+ years of analytics experience in supply chain – preferable industries hi-tech, consumer technology, CPG, automobile, retail or e-commerce supply chain.
• Master in Statistics/Economics or MBA or M. Sc./M. Tech with Operations Research/Industrial Engineering/Supply Chain
• Hands-on experience in delivery of projects using statistical modelling

Skills / Knowledge

• Hands on experience in statistical modelling software such as R/ Python and SQL.
• Experience in advanced analytics / Statistical techniques – Regression, Decision tress, Ensemble machine learning algorithms etc. will be considered as an added advantage.
• Highly proficient with Excel, PowerPoint and Word applications.
• APICS-CSCP or PMP certification will be added advantage
• Strong knowledge of supply chain management
• Working knowledge on the linear/nonlinear optimization
• Ability to structure problems through a data driven decision-making process.
• Excellent project management skills, including time and risk management and project structuring.
• Ability to identify and draw on leading-edge analytical tools and techniques to develop creative approaches and new insights to business issues through data analysis.
• Ability to liaison effectively with multiple stakeholders and functional disciplines.
• Experience in Optimization tools like Cplex, ILOG, GAMS will be an added advantage.