Mandatory Skills
SQL, PYTHON, Operations Research, Data Science, and Data Mining.
Client Interview Needed for Selection (Yes / No)
YES , Two coding rounds
JD (Pl share the Detailed Description, 1 liner JD will not work)
Data science Analyst with following JD.
Duties
- Identify business problems and solve them by using various numerical techniques, algorithms, and models in Operations Research, Data Science, and Data Mining.
- Tackle problems on a broad spectrum of areas: Supply Chain Optimization, Inventory & Capacity Planning, Process Design & Optimization, Financial Modeling, Demand Forecasting.
- Design and develop creative and innovative Business Intelligence/Analytic solutions from the data coming from various custom systems and databases.
- Partner with internal stakeholders to understand business requirements, work with cross-functional data and business teams across Enterprise Operations to build efficient and scalable datasolutions.
- Analyze current business processes using operational dashboards and identify levers for improving overall performance. Recommend and drive process changes based on robust analysis of operational data and user behavior.
- Collaborate with cross-functional data and business teams across Enterprise Operations to access and manipulate data, explain datagathering requirements, display results, and build efficient and scalable analytics solutions
- Define, compute, track, and continuously validate business metrics with descriptive and predictive analytics
- See beyond the data to identify solutions that will raise the bar for all things operations related. Need to be self starter
Requirements:
Bachelors or Master’s degree in Operations Research, Supply Chain Management, Computer Science, Systems Engineering, Mathematics, Statistics, Quantitative Finance or related field and 5 years of work experience in any analytics-related occupation.
Experience in:
- Building analytics solutions and developing algorithms for machine learning, statistics, mathematical programming, and simulation in industry and/or academia
- Business intelligence and data warehousing
- Data visualization tools, specifically Tableau and statistical analysis tools such as R or Python
- SQL development and statistical data analysis
- Building dashboards and utilizing data to build reporting solutions
- Handling large volumes of data, and performance tuning
- Developing with R/Python, SQL
- Familiarity with optimization software such as Gurobi/Xpress
- Simulation Modeling using Anylogic(Highly preferable), Arena, simpy or simmeR
- Solving problems by providing practical business insights from large, complex data sets
- Presenting technical content to general audiences