[Remote] Data Scientist Principal
Note: The job is a remote job and is open to candidates in USA. FedEx Dataworks is seeking a Data Scientist Principal to lead advanced analytics initiatives across the organization and design end-to-end machine learning solutions. This role involves mentoring data science teams, translating complex data into actionable insights, and driving innovation in data science and machine learning practices.
Responsibilities
- Lead and own high-impact data science initiatives within the DW 2.0 data monetization scope and other initiatives as needed, from problem framing through deployment and monitoring
- Apply advanced AI techniques (LLMs, reinforcement learning, graph ML, and optimization algorithms) to address complex, high-impact challenges across supply chain operations such as routing, inventory balancing, capacity planning, and risk mitigation
- Architect and develop scalable machine learning models (e.g., predictive, prescriptive, NLP, computer vision) for production
- Lead rapid prototyping and iterative experimentation: leverage modern AI stacks (Azure OpenAI, Vertex AI, LangChain, vector databases) to design lean experiments, measure impact, and iterate quickly while avoiding dependency bottlenecks
- Handle pressure with poise, balancing urgent requests with long-term project goals and ensuring reliable outcomes
- Build and operationalize end-to-end AI/ML systems, including LLM pipelines, prompt engineering strategies, fine-tuning, model evaluation, guardrails, and monitoring for performance, drift, and responsible AI compliance. Collaborate with engineering teams to integrate data pipelines, ensure model reliability, and optimize performance
- Define metrics and success criteria; perform rigorous statistical analysis, A/B testing, and AI model evaluation (hallucination detection, accuracy, latency, relevance) to validate system effectiveness
- Translate business objectives into analytical approaches, interpret results, and present clear storytelling and data-driven recommendations to senior leadership
- Mentor and coach junior and mid-level data scientists; establish best practices in coding, model development, and documentation
- Drive innovation by researching and prototyping emerging techniques, tools, and frameworks in machine learning, deep learning, and AI
- Partner with legal, security, and data governance teams to ensure data usage adheres to privacy, security, and contractual obligations; develop compliant mechanisms to enable safe, fast experimentation (see recommended approaches below)
- Communicate results and recommendations clearly to senior leadership and cross-functional stakeholders; translate complex analyses into actionable business insights
- Cultivate deep domain expertise in FedEx data and tools, taking direction from senior team members and contributing to knowledge sharing
- Collaborate with business partners and subject matter experts to translate complex questions into clear analytical insights and present findings effectively
Skills
- Extensive knowledge in advanced data science and machine learning methods, including the iterative development of analysis pipelines to provide insights at scale
- Strong experience as a leader of multi-functional project teams
- Excellent interpersonal skills and the ability to present and communicate effectively to executive audiences. A related advanced degree may offset the related experience requirements
- Proficiency in SQL, Python, and/or R
- Foundational knowledge of machine learning libraries (scikit-learn, XGBoost, TensorFlow, or PyTorch)
- Hands-on experience with Azure (e.g., Data Factory, Synapse, Databricks, Blob Storage) and / or Google Cloud Platform (GCP) and its core analytics/ML services (BigQuery, Vertex AI, Dataflow, Pub/Sub)
- Demonstrated ability to leverage various APIs for data manipulation and integration
- Experience with at least one data visualization tool or package (e.g., Tableau, Power BI, Spotfire, Shiny, Plotly, Matplotlib, Seaborn)
- Solid understanding of ETL concepts, relational databases (e.g., Teradata, Oracle), and working with large-scale datasets
- Proficiency with version control (git) and familiarity with MLOps/DevOps principles (CI/CD, model tracking, deployment workflows)
- Demonstrated superior analytical skills with diverse analytics, data types, and statistical software and applications
- Outstanding Interpersonal skills, written, and oral communication skills
- Proven Leadership skills
- Master's degree or equivalent in a quantitative discipline required
- Proven expert and nine (9) years work experience in innovative measurement and analysis, quantitative business problem solving, solutions implementation, operations analysis, marketing analysis, simulation development and/or predictive analytics
- Proven background with enterprise AI solutions, agentic architectures, or scalable LLM platforms
- Proficiency in Power BI for building interactive dashboards, reports, and data visualizations
- Experience in your industry domain (e.g., finance, healthcare, e-commerce)
- Familiarity with MLOps practices and tools (MLflow, Kubeflow, Airflow)
- Prior experience leading cross-functional teams and managing stakeholder relationships
- Publications or contributions to open-source projects in machine learning or data science
Benefits
- The Company offers eligible employees health, vision and dental insurance, retirement, and tuition reimbursement.
Company Overview