Senior Data Scientist – Digital Fulfillment T+

Job description

**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.

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 different voices and lifts each other up.

Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful.

**Overview about TII**

At Target, we have a timeless purpose and a proven strategy.

And that hasn’t happened by accident.

Some of the best minds from different 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.

**Pyramid Overview**

A role with Target Data Science & Engineering means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale.

Whether you join our Statistics, Optimization or Machine Learning teams, you’ll be challenged to harness Target’s impressive data breadth to build the algorithms that power solutions our partners in Marketing, Supply Chain Optimization, Network Security and Personalization rely on.

**Team Overview**

Our **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 network.

**Position Overview:**

As a **Senior 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.

+ Develop a **strong understanding of business and operational processes** within Target’s Supply chain and Target Marketplace
+ 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 machine learning, optimization/statistical/Discrete event simulation models** to solve problems in promise, allocation and digital fulfilment on large data
+ **Integrate models** into **production code base** with robust test coverage
+ Adopt modular architecture and good software development/engineering practices to enhance the overall product performance
+ Produce clean, efficient code based on specifications
+ Coordinate the analysis, troubleshooting and resolution of issues in the models and software
+ Generate analyses and other project artefacts to document, archive, and communicate work and outcomes
+ Build self-service tools for error detection, diagnosis and predictive metrics.

**About You**

+ Bachelors/MS/PhD in Mathematics, Statistics, Operations Research, Industrial Engineering, Physics, Computer Science or other related fields
+ 4+ years of relevant experience
+ Background in **supply chain or ecommerce** 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 using standard ML Ops framework and tools
+ **Good understanding of** data structures and algorithms
+ 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

**Know More About Us here:**

+ **Life at Target** - https://india.target.com/
+ **Benefits** - https://india.target.com/life-at-target/workplace/benefits
+ **Culture-** https://india.target.com/life-at-target/belonging

Required Skill Profession

Other General