At Tesla, we move at warp speed and warehousing, distribution and logistics is at the forefront of the evolution of Tesla’s Service Parts Supply Chain as we embark on transformational change in the coming months. We have an ambitious vision and a complex portfolio of programs that enable Tesla’s future.
As a Sr. Data Scientist on the Distribution Strategy & Execution team, you will be responsible for architecting and prescribing evolutionary roadmap for Tesla’s global network for Distribution Centers for Service Parts Supply Chain. You will have full ownership over end-to-end process from identification of opportunities and bottlenecks in the supply chain to delivery of solutions. You’ll drive projects across multiple geographies – NAMR, EMEA, and APAC – and touch multiple domains – distribution, transportation, financial, and inventory management. We are looking for a leader who is goal-oriented, results driven, and data-centric.
· Architect the NAMR network of distribution centers, forward stocking locations, crossdock nodes and overall expansion plan for Tesla’s Service and Energy business units.
· Analyze and determine the optimal solutions for end-to-end flow of parts – including logistics route and mode design, inventory optimization, capacity planning, cross-docking operations, etc.
· Design, develop and implement highly scalable optimization models for inbound transportation and outbound transportation including last mile logistics design aimed at reducing order-to-delivery lead times from days to hours with economic feasibility.
· Provide thought leadership in analytics, modeling, and drive to promote team’s capability and output. Mentor team members and collaborate internally and externally to solve business problems.
· Translate quantitative research and analysis into actionable insights, prepare visualizations and present findings with influential storytelling.
· Develop and program manage implementation of solutions and business processes that are optimized for speed, accuracy, cost efficiency, capacity, and flexibility.
· Develop decision support systems, tools, and models that are scalable and reproducible to assist in strategizing growth and decision making for Tesla supply chain capabilities.
· Simulate and conduct sensitivity analysis to stress test existing network and future models to identify operational bottlenecks and risks.
· Formulate and analyze what-if scenarios, design and evaluate experiments, alternate and conceptual models.
· Champion the use of Operations Research and Data Science concepts, techniques, and best practices.
· Master’s degree or PhD. in Operations Research, Data Science, Industrial Engineering, Systems Engineering, Applied Math in Logistics, Supply Chain Management or equivalent.
· 5+ years of experience in supply chain operations, logistics, E-commerce, or manufacturing.
· Programming skills with at least one object-oriented language (e.g. Java) and one scripting language (e.g. Python)
· Experience with statistical software (R), database languages (SQL), simulation tools (ARENA, AnyLogic, FlexSim), data visualization tools (e.g., Tableau, Power BI, d3.js), predictive modeling/ ML tools (Scikit Learn, R) and solvers (Gurobi, CPLEX, or Xpress)
· Experience working with advanced planning systems and tools like Llamasoft, AnyLogistix, i2/JDA, Oracle ASCP, SAP APO etc.
· Proficient in concepts of Operations Research and Data Science like mathematical programming (LP, Non-LP, MIP), Queuing Theory, Simulation, Long Term Forecasting, Anomaly Detection, Clustering, etc.
· Knowledgeable in modeling heuristics, best practices, and effective solutions from within the industry or derived from other industries.
· Ability to thrive in a fast-moving and constantly evolving high growth environment.
· Comfortable in an environment with unstructured, incomplete, and ambiguous data.
. Experience creating end to end ETL pipeline is a plus