Job Description
Location : Chennai - WFO
CTC : Open
NOTICE PERIOD: IMMEDIATE or Short Notice
Mandatory Skill
Ideally for this role, we needed someone with good Optimization experience / knowledge about optimization tools like Pulp/Gurobi/CPLex.
Sr Data Scientist- Operations Research
- 10+ years in Data Science, with at least 3 years in the Marketing Analytics domain.
- Advanced degree in Mathematics, Statistics, Analytics, Operational Research, or related fields.
- Proficient in machine learning, deep learning, NLP, and AI model development using Python, R, Scala, or similar languages.
- Familiarity with deep learning applications and tools (TensorFlow, Theano, etc.), and a solid grasp of neural networks, including computer vision nets.
- Proven ability in problem-solving with a quantitative, scientific approach.
- Knowledge of cloud environments (AWS/GCP/Azure/Nvidia) and MLOPS.
About the Role: We are seeking a highly motivated and talented Operations Research Scientist to join our Data Science team. In this role, you will apply your expertise in mathematical modeling, optimization, and data analysis to optimize our retail fulfillment, delivery, and inventory management processes. You will collaborate closely with cross-functional teams to identify and solve complex logistical challenges, developing and implementing data-driven solutions that enhance efficiency, cost-effectiveness, and customer satisfaction.
Responsibilities
Partner with stakeholders across fulfillment centers, transportation, and inventory management to gain a deep understanding of operational challenges and opportunities for improvement.
Work with a team of talented Data Scientists and Engineers to combine predictive and prescriptive models into production solutions.
Develop quantitative models using optimization techniques, simulation, and machine learning to address critical issues in areas such as:
Fulfillment center operations: optimizing order picking, packing, waving, and routing and labor planning within fulfillment centers. Delivery logistics: selecting routes and schedules for transfers between distribution centers to optimize trade-offs between transportation costs and inventory placement costs.
Inventory management: optimizing product assortments and stocking levels across locations to meet demand while minimizing stockouts and shipments per order.
Network optimization: selecting the optimal network of distribution centers to ensure maximum demand coverage at minimum cost.
Analyze large datasets from various sources, including customer orders, warehouse operations, and transportation data, to extract valuable insights for decision-making.
Design and conduct experiments to validate the effectiveness of proposed solutions and measure their impact on key performance indicators (KPIs).
Communicate complex findings and recommendations effectively to both technical and non-technical audiences through presentations, reports, and visualizations.
Stay up-to-date on the latest advancements in operations research methodologies and software tools relevant to retail logistics.
Continuously strive to improve and innovate our fulfillment, delivery, and inventory management processes.
Qualifications
A Masters degree in Operations Research, Industrial Engineering, Mathematics, Analytics, or a closely related field, or a Bachelor's degree with significant experience in a relevant field.
At least two years of experience applying mathematical modeling techniques, including linear programming, mixed-integer programming, and simulation, to solving business problems; preferably in the retail or logistics industry.
Experience in working with large datasets and utilizing statistical analysis and machine learning tools (e.g., Python, R, SQL).
Excellent written and verbal communication skills, with the ability to present complex information in a clear and concise manner.
Ability to work independently and manage multiple projects simultaneously while collaborating effectively within a team environment
