Data Science and Operations Research Enablement Principal

Federal Express Corporation•Moon Township, PA

2d•$9,208 - $20,872•Remote

About The Position

A Principal in Data Science and Operations Research (DSOR) Enablement is a senior-level role responsible for leading the integration of advanced analytics and operations research methodologies across the organization, driving optimization of business processes and decision-making. They collaborate with cross-functional teams to identify strategic opportunities and implement data-driven solutions that align with organizational goals. With a deep understanding of both business operations and technical methodologies, they provide strategic direction, mentorship, and technical expertise, empowering DSOR practitioners to deliver impactful insights and solutions. They play a key role in influencing leadership through effective communication, ensuring that DSOR initiatives deliver impactful, value-driven outcomes.

Requirements

Deep conceptual understanding of Generative AI architectures (LLMs, RAG, prompt engineering), traditional machine learning, and Operations Research methodologies.
Strong working knowledge of enterprise data ecosystems, including cloud platforms (e.g., Azure, GCP, AWS), foundational languages (Python, SQL), and AI/MLOps deployment concepts.
Proven ability to guide and oversee the translation of complex algorithms, statistical models, and Data Science proofs-of-concept into scalable engineering requirements and business-value metrics.
Mastery of Agile/Scrum frameworks and tools (e.g., Jira, ADO) specifically tailored for research-oriented data science teams.
Deep knowledge of product discovery frameworks, user-centric design, and strategic roadmapping to prioritize and build what delivers the highest ROI.
Proven track record of driving innovation initiatives, successfully transitioning early-stage technical research and proofs-of-concept into structured, launch-ready program plans.
Exceptional capability to influence, align, and communicate complex technical progress to senior executives, business partners, and technical leads.
Natural ability to mobilize and mentor cross-functional matrixed teams, fostering a culture of curiosity, rapid prototyping, and continuous delivery.
Bachelor’s degree or equivalent in Data Science, Operations Research, Engineering, Business Administration, Business Analytics, or related discipline.
Five to eight (5 - 8) years of experience in working with teams in analytics, data science, operations research, engineering or a related field, with demonstrated leadership in managing teams and executing complex projects.
Practitioner or practitioner-adjacent experience in analytics, data science, operations research, or a related fields inclusive of prototyping and rapid experimentation.

Nice To Haves

Advanced degree (Master’s or Ph.D.) in Data Science, Operations Research, Engineering, Business Analytics, or a related quantitative field.
Prior experience leading analytics, AI product initiatives, or supply chain modernization efforts within complex logistics, customs clearance, or highly regulated operational environments.

Responsibilities

Develop data-driven product strategies that achieve strategic objectives, collaborating with cross-functional business stakeholders and technical partners to assess opportunities and define requirements.
Lead cross-functional teams through the Product Discovery to determine how to execute against the vision, what to prioritize and build.
Lead agile scrum ceremonies for teams of data scientists.
Drive execution and ensure the team delivers the desired business outcomes efficiently.
Engage with market trends and conduct ongoing evaluations of comparable product offerings, identifying opportunities for refining the product strategy and improving the customer experience.
Communicate plans and progress to key internal partners and executives, soliciting and incorporating feedback.
Provide strategic guidance, setting clear priorities, and ensuring effective execution of Clearance Data Science and Generative AI projects from hypothesis to deliverable.
Mobilize and mentor cross-functional teams, fostering a culture of curiosity, experimentation, and continuous improvement.
Support the design of user-centric products that align with business goals, enhancing decision-making and user engagement.
Track progress and ensure accountability for project milestones, delivering impactful solutions that maximize the value of Clearance Data Science and Generative AI initiatives.
Bridge the gap between AI experimentation and engineering execution, transforming raw Data Science proofs-of-concept into fully scoped, launch-ready program plans for development teams.