Job Profile Summary : Takes ownership and responsibility over major data science initiatives. Advances ACCs’ broad capabilities to use and deploy cutting edge data science and machine learning tools and methods in ACCs projects, platforms and products. Simultaneously work to keep ACCs on the leading edge by understanding and implementing the very latest and most sophisticated methods and tools for grappling with extremely large scale and complex problems. Lead modeling and development to support operations initiatives, strategic programs and new products/solutions, through the use of advanced descriptive, diagnostic, predictive, prescriptive and ensemble modeling, advanced statistical techniques, and complex mathematical modeling/tool development. Develops solutions supporting the movement of data and information assets following API-First / Service-Oriented Architecture principles. Leverages proficiency in ML Ops, CI/CD processes and machine learning / data engineering practices to ensure sustainable model development and provide recommendations on highly complex problems. Mentors less senior team members to drive results. Leads and works with cross-functional teams. - Job Description : Responsibilities :

- Understanding in depth both the business and technical problems ACCs aims to solve
- Exploring data and crafting models to answer core business problems that may not have a common blueprint
- Leading the invention of new approaches and algorithms for tackling data intensive problems
- Pioneering R&D; efforts to rapidly understand and assimilate state of the art methods
- Scaling up from “laptop-scale” to “cluster scale” problems by leading efforts to standardize and industrialize solutions
- Delivering tangible value very rapidly, collaborating with diverse teams of varying disciplines




- Interacting with senior technologists from the broader enterprise and outside of FedEx (partner ecosystems and customers) to create synergies and identify opportunities for improvement
- Codifying best practices for future reuse in the form of accessible, reusable patterns, templates, and code bases

Skills and Abilities

- Technical background in computer science, data science, machine learning, artificial intelligence, statistics or other quantitative and computational science
- A compelling track record of Data Science / Engineer expertise, designing and deploying large scale technical solutions, which deliver tangible, ongoing value
- Direct experience having built and deployed robust, complex production systems through Cloud technologies that implement modern, data scientific methods at scale

Ability to context-switch, to provide support to dispersed teams which may need an “expert hacker” to unblock an especially challenging technical obstacle

Demonstrated ability to deliver technical projects with a team, often working under tight time constraints to deliver value

An ‘engineering’ mindset, willing to make rapid, pragmatic decisions to improve performance, accelerate progress or magnify impact

Ability to work with distributed teams on code-based deliverables using version control

- Solid theoretical grounding in the mathematical core of the major ideas in data science




- Expert level understanding of a class of modelling or analytical techniques, often supported by Masters
- Deep fluency in the mathematical ‘primitives’ and generalizations of data science - e.g., expertise in Linear Algebra, and Vector Calculus
- Use of agile and devops practices for project and software management including CI/CD; process improvement and quality management experience (e.g., Lean, Six Sigma, QDM expert)
- Demonstrated expertise in working with some of the following common languages and tools: SKLearn, XGBoost, Tensorflow, Pytorch, MLlib and other core ML frameworks

Python and other contemporary programming languages

MLFlow, Databricks, AWS, Azure and other data tools and frameworks

CPLEX, Gurobi and other similar optimization modeling packages - Minimum Qualifications

- Master’s Degree or equivalent in computer science, operations research, statistics, applied mathematics or related quantitative discipline. Directly related PhD preferred.
- Extensive knowledge in advanced data science, statistical analysis, and machine learning methods, including the iterative development of analysis pipelines to provide insights at scale.
- Extensive experience conducting end-to-end analyses, including data gathering and requirements specification, processing, analysis and presentation. Strong familiarity with the transportation industry, competitors, and evolving technologies.
- Experience providing leadership in a general planning or consulting setting. Experience as a leader or a senior member of multi-functional project teams.
- Strong human relations, organizational / time management, project management, and software development skills.
- Excellent interpersonal skills and the ability to present and communicate effectively to

📌 Data Scientist-senior Ii (Chennai)
🏢 Fedex AMEA
📍 Chennai