Lead Data Scientist- Supply Chain Tower 02, Manyata Embassy Business Park India

5 days ago


Bengaluru, India Target Full time
About us:

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. At Target, we have a timeless purpose and a proven strategy and that hasn’t happened by accident. Some of the best minds from diverse backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Target’s global team and has more than 4,000 team members supporting the company’s global strategy and operations.Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values diverse backgrounds. We believe your unique perspective is important, and you'll build relationships by being authentic and respectful. At Target, inclusion is part of the core value. We aim to create equitable experiences for all, regardless of their dimensions of difference. As an equal opportunity employer, Target provides diverse opportunities for everyone to grow and winPyramid OverviewOur Supply Chain Data Science team oversees the development of state-of-the-art mathematical techniques to help solve important problems for Target’s Supply Chain e.g. identifying the optimal quantities and positioning of inventory across multiple channels and locations, planning for the right mix of inventory investments vs guest experience, Digital order Fulfillment planning, transportation resource planning, etc. As a Data Scientist in Digital fulfillment Planning space, you will have the opportunity to work with Product, Tech and business partners to solve retail challenges at scale for our fulfillment networkTeam OverviewA role with the Data Science team means building scalable data science products in support of the ever-changing supply chain landscape. This will mean being more intelligent, automated and algorithmic in our decision-making. Evaluating product flow from vendor to distribution center, and to the stores across the first mile, middle mile and last mile, with focus on inventory modeling and replenishment, to improve operating efficiencies both within 4 walls of distribution center and across the network. So, we’re looking for exceptional people who are proactive, creative, independent, innovative and comfortable working in varying degrees of ambiguity. Are you a creative problem-solver who seeks root cause, simplifies problems, quickly identifies solutions, commits to a plan and then positively influences others to execute it? If so, you will have success on this dynamic team.

As a Lead Data Scientist at Target you will get an opportunity design, develop, deploy and maintain data science models and tools. You’ll work closely with applied data scientists, data analysts and business partners to continuously learn and understand evolving business needs. You’ll also collaborate with engineers and data scientists on peer teams to build and productionize fulfillment solutions for our supply chain/logistics needs.In this role as a Lead Data Scientist, you will:Develop a strong understanding of business and operational processes within Target’s Supply chain.

Develop an in-depth understanding of the various systems and processes that influence Digital order fulfillment speed & costs.

Develop and deploy scalable and reproducible data science models for answering variety of business problems

Work hands on and actively partner across the team – defining business problem, formalize the problem algorithmically, data discovery to insights/predictions and prototype solutions

Analyze data to identify and propose feature enhancements. Design and implement features to improve scope of the product.

Develop and deploy modules to run simulations for testing and validating multiple scenarios to evaluate the impact of various fulfillment strategies

Add new capabilities and features to the simulation framework to reflect the complexities of an evolving digital fulfillment network

Adopt modular architecture and good software development/engineering practices to enhance the overall product performance and guide other team members

Produce clean, efficient code based on specifications

Work with the team to build and maintain complex software systems and tools

Coordinate the analysis, troubleshooting and resolution of issues in the models and software

Develop machine learning, optimization/statistical/Discrete event simulation models to answer problems for replenishment, inventory positioning/planning, product flow etc on large data. Integrate models into production code base with robust test coverage

Generate analyses and other project artefacts to document, archive, and communicate work and outcomes

Anticipate and Evaluate impact of Data science solutions on related projects as part of the developing complex data science algorithm/solutions for various business problems

Build self-service tools for error detection, diagnosis and predictive metrics.

Requirements:MS/PhD in Mathematics, Statistics, Operations Research, Industrial Engineering, Physics, Computer Science or other related fields

8+ years of relevant experience

Background in supply chain will be preferable but not mandatory

Experience in delivering quick POCs with iterative improvement in product outcomes

Strong analytical thinking and data visualization skills. Ability to creatively solve business problems, innovating new approaches where required

Hands-on experience in deploying ML models with large-scale impact in commercial setting

Deep understanding of data structures and algorithms

Experience working with large event-driven distributed systems and multi-threaded applications

Highly proficient in programming skills in Python, SQL, Hadoop/Hive, Spark. Additional knowledge of Scala, R, Java desired but not mandatory

Extensive experience in developing, refining, validating, deploying ML models to deliver measurable business outcomes

Good working knowledge of mathematical and statistical concepts, MILP, optimization, algorithms and computational complexity, data analysis, data mining, forecasting/predictive modeling, simulations, visualizations, and application of same in a variety of business problems

Excellent written and verbal communication skills

Able to produce reasonable documents/narrative suggesting actionable insights and recommendations

Passion for solving interesting and relevant real-world problems using Data science approach

Self-driven and results oriented. Willing to stretch to meet tight timelines.

Strong team player with ability to collaborate effectively across geographies/ time zones.

Ability to think quick and structure conversations in group setting

Useful Links-Life at Target-Benefits-Culture-

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