Full-Time Data Scientist

About FedEx Dataworks:

Born out of FedEx, a pioneer that ships nearly 20 million packages a day and manages endless threads of information, FedEx Dataworks is an organization rooted in connecting the physical and digital sides of our network to meet today's needs and address tomorrow's challenges.

We are creating opportunities for FedEx, our customers, and the world at large by:

• Exploring and harnessing data to define and solve true problems
• Removing barriers between data sets to create new avenues of insight
• Building and iterating on solutions that generate value
• Acting as a change agent to advance curiosity and performance

At FedEx Dataworks, we are making supply chains work smarter for everyone.

Summary:

Takes ownership and responsibility over major data science initiatives. Advances Dataworks' broad capabilities to use and deploy cutting edge data science and machine learning tools and methods in Dataworks projects, platforms and products. Simultaneously works to keep Dataworks 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. Leads 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 responsibilities:

The Data Scientist plays a pivotal role, focused on creating and driving data science innovation within Dataworks, helping define and build the Dataworks organization, and enabling the delivery of key business initiatives. S/he acts as a universal translator" between IT, business, software engineers and data engineers, collaborating with these multi-disciplinary teams. The Data Scientist will contribute to the creation and adherence of technical standards for data science and machine learning, including the design and construction of reusable data assets. S/he will work with large data sets and solve difficult analytical problems, applying advanced methods. S/he will lead the creation and implementation of solutions from concept to production, using current and emerging technologies to evaluate trends and develop actionable insights and recommendations. Day-to-day, s/he will be deeply involved in code reviews and large-scale deployments. S/he will also provide mentorship and guidance to junior data scientists to support the continued training and up-skilling of the Data Science team.

Key Areas of Focus:

Understanding in depth both the business and technical problems Dataworks 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/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- or Doctoral-level research in the subject

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, Scala, R, C++, Java and other modern programming languages

MLFlow, Databricks, Spark, Kafka, Hive, Hadoop and other data tools and frameworks

CPLEX, Gurobi and other similar optimization modeling packages

Minimum qualifications:

Data Scientist 

Bachelors Degree with at least One year experience or Master's Degree or equivalent in computer science, operations research, statistics, applied mathematics or related quantitative discipline. Strong knowledge in advanced data science and machine learning tools and methods, including the iterative development of analysis pipelines to provide insights at scale. Strong knowledge and experience in conducting end-to end analyses, including data gathering and requirements specification, processing, analysis, and presentations. Strong understanding of the transportation industry, competitors, and evolving technologies. Experience as a member of multi-functional project teams. Strong oral and written communication skills.