NAV-BI Developer
at Product based company specializes into architectural product
Must/Good to Have Details :
- Must have 3-7 years of IT experience with end-to-end design and development using Microsoft BI Products.
- Extensive experience in designing and developing Stored Procedures/functions in MS SQL Azure and Microsoft Cloud based technologies.
Must have :
1) Working experience in Azure SQL , Microsoft Dynamics NAV/365 Business Central Reporting and data.
2) Experience with data warehouse design, OLAP and ETL framework.
3) Experience in NAV Report Builder and Office 365 integration with dynamics Apps is a plus.
4) Analytical mind with the ability to manage multiple projects and adjust quickly to changing priorities.
5) Programming or scripting experience and knowledge of SDLC preferred.
6) Excellent Communication Skills :
Good to have :
1) Experience in construction and manufacturing process, a plus.
2) Proficient in MS Office 365 products.
3) Exposure with SCRUM/Agile methodologies and practice, a plus.
Subodh Popalwar
Software Engineer, Memorres
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Data AnalyticsThe client is an industry leader in CRM messaging solutions on SAS platform. They work with global customers across many industries including contact centers, financial services, higher education, retail, staffing, wellness, and more. Our customers range from small and mid-size businesses to large global enterprises.
As a Director of Information Systems , you will oversee and manage the organization's information technology (IT) and information systems operations. You will leverage Information systems, tools, data and analytics to support stakeholders across Product, Sales, Marketing, Operations, and Finance.
You will lead and directly manage a team of data analysts, while partnering with other teams across the organization and directly report to the COO.
Key Responsibilities:
● Collaborate with senior management to understand their data requirements and develop data management strategy aligned with the organization's goals and objectives. Define KPI around data and lead the initiatives.
● Develop and implement data architecture, which is a blueprint for how data is organized and stored within an organization. Provide necessary interventions to ensure critical business decisions are taken well in time.
● Implement master data management (MDM) processes and solutions to establish a single source of truth for critical data entities. Define data hierarchies, data models, and data stewardship responsibilities. Oversee the maintenance and synchronization of master data across systems.
● Work with other departments to identify data trends and patterns that support the organization’s objectives. This will include using data visualization tools, such as dashboards and charts, to help identify trends and insights.
● Evaluate, select, and manage vendors and service providers to ensure effective delivery of services and solutions.
● Build and manage a high-performing systems and information team.Set clear goals, performance expectations, and KPIs for the team, conducting regular performance reviews and providing guidance/feedback.
Qualifications and Skills:
● Bachelor's degree in computer science, information systems, or a related field.
● Experience ( 7-10 years) in systems management, information technology, or a related role within the SaaS industry.
● Strong knowledge of data analysis methods, tools, and best practices. Experience in Salesforce and Power BI is a must.
● Ability to do requirements analysis of business processes for efficiency, data accuracy, data control, and make data-driven recommendations
● Excellent problem-solving and decision-making skills, attention to detail, with the ability to prioritize tasks and manage multiple projects simultaneously.
● Knowledge of industry best practices and emerging trends in systems management and information technology.
● Demonstrated ability to lead and manage cross-functional teams, fostering collaboration and driving results.
● Strong communication and interpersonal skills, with the ability to effectively communicate technical concepts to non-technical stakeholders.
Data Science
Machine Learning (ML)
Pythono You’re both relentless and kind, and don’t see these as being mutually
exclusive
o You have a self-directed learning style, an insatiable curiosity, and a
hands-on execution mindset
o You have deep experience working with product and engineering teams
to launch machine learning products that users love in new or rapidly
evolving markets
o You flourish in uncertain environments and can turn incomplete,
conflicting, or ambiguous inputs into solid data-science action plans
o You bring best practices to feature engineering, model development, and
ML operations
o Your experience in deploying and monitoring the performance of models
in production enables us to implement a best-in-class solution
o You have exceptional writing and speaking skills with a talent for
articulating how data science can be applied to solve customer problems
Must-Have Qualifications
o Graduate degree in engineering, data science, mathematics, physics, or
another quantitative field
o 5+ years of hands-on experience in building and deploying production-
grade ML models with ML frameworks (TensorFlow, Keras, PyTorch) and
libraries like scikit-learn
o Track-record in building ML pipelines for time series, classification, and
predictive applications
o Expert level skills in Python for data analysis and visualization, hypothesis
testing, and model building
o Deep experience with ensemble ML approaches including random forests
and xgboost, and experience with databases and querying models for
structured and unstructured data
o A knack for using data visualization and analysis tools to tell a story
o You naturally think quantitatively about problems and work backward
from a customer outcome
What’ll make you stand out (but not required)
o You have a keen awareness or interest in network analysis/graph analysis
or NLP
o You have experience in distributed systems and graph databases
o You have a strong connection to finance teams or closely related
domains, the challenges they face, and a deep appreciation for their
aspirations
Machine Learning (ML)Data SciencePythonclosely with the Kinara management team to investigate strategically important business
questions.
Lead a team through the entire analytical and machine learning model life cycle:
Define the problem statement
Build and clean datasets
Exploratory data analysis
Feature engineering
Apply ML algorithms and assess the performance
Code for deployment
Code testing and troubleshooting
Communicate Analysis to Stakeholders
Manage Data Analysts and Data Scientists
Data AnalyticsOur client is a vertical fintech play focused on solving industry-specific financing gaps in the food sector through the application of data. The platform provides skin-in-the-game growth capital to much-loved F&B brands. Founded in 2019, they're VC funded and based out of Singapore and India-Bangalore.
Founders are the alumnus of IIT-D, IIM-B and Wharton. They have 12+ years of experience as Venture capital and corporate entrepreneurship at DFJ, Vertex, InMobi, VP at Snyder UAE, investment banking at Unitus Capital - leading the financial services practice, and institutional equities at Kotak. They've a team of high-quality professionals coming together for this mission to disrupt the convention.
As a Data Analyst - Underwriting & Risk, you will be developing a first of its kind risk engine for revenue-based financing in India and automating investment appraisals for the company's different revenue-based financing products
What you will do:
- Identifying alternate data sources beyond financial statements and implementing them as a part of assessment criteria.
- Automating appraisal mechanisms for all newly launched products and revisiting the same for an existing product.
- Back-testing investment appraisal models at regular intervals to improve the same.
- Complementing appraisals with portfolio data analysis and portfolio monitoring at regular intervals.
- Working closely with the business and the technology team to ensure the portfolio is performing as per internal benchmarks and that relevant checks are put in place at various stages of the investment lifecycle.
- Identifying relevant sub-sector criteria to score and rating investment opportunities internally.
What you need to have:
- Bachelor’s degree with relevant work experience of at least 3 years with CA/MBA (mandatory).
- Experience in working in lending/investing fintech (mandatory).
- Strong Excel skills (mandatory).
- Previous experience in credit rating or credit scoring or investment analysis (preferred).
- Prior exposure to working on data-led models on payment gateways or accounting systems (preferred).
- Proficiency in data analysis (preferred)
- Good verbal and written skills.
Data Science
R ProgrammingPythonMachine Learning (ML)Data ScienceMachine Learning (ML)PythonR ProgrammingTiger Analytics is a global AI & analytics consulting firm. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modeled around expertise and mutual respect with a team first mindset. Working at Tiger, you’ll be at the heart of this AI revolution. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire.
We are headquartered in the Silicon Valley and have our delivery centres across the globe. The below role is for our Chennai or Bangalore office, or you can choose to work remotely.
About the Role:
As an Associate Director - Data Science at Tiger Analytics, you will lead data science aspects of endto-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and client interaction.
• Work closely with internal teams and client stakeholders to design analytical approaches to
solve business problems
• Develop and enhance a broad range of cutting-edge data analytics and machine learning
problems across a variety of industries.
• Work on various aspects of the ML ecosystem – model building, ML pipelines, logging &
versioning, documentation, scaling, deployment, monitoring and maintenance etc.
• Lead a team of data scientists and engineers to embed AI and analytics into the client
business decision processes.
Desired Skills:
• High level of proficiency in a structured programming language, e.g. Python, R.
• Experience designing data science solutions to business problems
• Deep understanding of ML algorithms for common use cases in both structured and
unstructured data ecosystems.
• Comfortable with large scale data processing and distributed computing
• Excellent written and verbal communication skills
• 10+ years exp of which 8 years of relevant data science experience including hands-on
programming.
Designation will be commensurate with expertise/experience. Compensation packages among the best in the industry.
Data ScienceMachine Learning (ML)R ProgrammingPythonKey Responsibilities:
- Partnering with clients and internal business owners (product, marketing, edit, etc.) to understand needs and develop models and products for Kaleidofin business line.
- Good understanding of the underlying business and workings of cross functional teams for successful execution
- Design and develop analyses based on business requirement needs and challenges.
- Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, hyperparameter tuning, ensembling etc.
- Providing statistical analysis on custom research projects and consult on A/B testing and other statistical analysis as needed. Other reports and custom analysis as required.
- Identify and use appropriate investigative and analytical technologies to interpret and verify results.
- Apply and learn a wide variety of tools and languages to achieve results
- Use best practices to develop statistical and/ or machine learning techniques to build models that address business needs.
- Collaborate with the team to improve the effectiveness of business decisions using data and machine learning/predictive modeling.
- Innovate on projects by using new modeling techniques or tools.
- Utilize effective project planning techniques to break down complex projects into tasks and ensure deadlines are kept.
- Communicate findings to team and leadership to ensure models are well understood and incorporated into business processes.
Skills:
- 2+ year experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms.
- Machine Learning Algorithms: Crystal clear understanding, coding, implementation, error analysis, model tuning knowledge on Linear Regression, Logistic Regression, SVM, shallow Neural Networks, clustering, Decision Trees, Random forest, Boosting trees, Recommender Systems, ARIMA and Anomaly Detection. Feature selection, hyper parameters tuning, model selection and error analysis, ensemble methods.
- Strong with programming languages like Python and data processing using SQL or equivalent and ability to experiment with newer open source tools
- Experience in normalizing data to ensure it is homogeneous and consistently formatted to enable sorting, query and analysis.
- Experience designing, developing, implementing and maintaining a database and programs to manage data analysis efforts.
- Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE)
- Experience in risk and credit scoring domains preferred
Data ScienceR ProgrammingPython
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Software Engineer, Memorres