Data Science Lead - Forecasting

What your main responsibilities are

Role Overview: FedEx is looking for an experienced Data Scientist with at least 8 years of experience to join our Data Science & Corporate Strategy team. In this crucial role, you will be instrumental in designing and building machine-based forecasting models to accurately predict demand and revenue. You will work at the intersection of data, technology, and business, collaborating with cross-functional and cross-regional teams to drive data analysis, create strategy logic, and implement high-impact forecasting solutions. As a technical leader, you will provide clear requirements to technology teams and communicate seamlessly with global stakeholders to ensure our data strategies deliver the best possible customer experience.

Responsibilities

Key Responsibilities

Customer Analytics & Insights:

• Model Development: Design, build, and deploy robust machine learning-based forecasting models to predict demand and revenue.
• Strategic Collaboration: Work closely with cross-functional and cross-regional teams to lead data analysis, monitoring, and forecasting initiatives.
• Implementation & Logic: Create the underlying logic for new data strategies and oversee their end-to-end implementation.
• Technical Leadership: Provide clear, actionable requirements to junior data scientists and technology teams regarding data attributes, model specifications, and platform needs.
• Stakeholder Communication: Engage and communicate with global stakeholders, translating complex technical models into clear business value to ensure the delivery of a superior customer experience.

Predictive Modeling & Data Science:

• Design, develop, and deploy advanced predictive models for customer churn, customer growth, loyalty, propensity scoring, and high-value customer identification.
• Lead the application of descriptive, diagnostic, predictive, prescriptive, and ensemble modeling techniques to solve complex business challenges.
• Design and evaluate controlled experiments and test-and-learn frameworks to measure the effectiveness of business initiatives and customer interventions.
• Stay at the forefront of emerging data science methodologies, technologies, and AI/ML advancements, driving innovation within the organization.

Required Skills & Qualifications

Core Technical Skills

• Programming & Environments: High proficiency in Python, PySpark, BigQuery, and Google Colab.
• Cloud Platforms: Deep expertise in Google Cloud Platform (GCP) is preferred; experience with Microsoft Azure is a strong plus.
• Data Visualization: Strong capability in Power BI (PBI) is preferred; experience with Looker Studio is optional but beneficial.

Advanced Engineering & Operations

• Machine Learning Operations: Extensive experience with MLOps practices for deploying, monitoring, and maintaining models in production.
• Version Control & Deployment: Proficiency in using GitHub and building/managing CI/CD pipelines for seamless integration and delivery.
• Emerging Technologies: Knowledge of or hands-on experience with Agentic AI and related advanced AI frameworks.

Leadership & Team Development-

• Lead cross-functional analytics initiatives from problem definition through solution delivery and business adoption.
• Mentor and develop junior data scientists and analysts, fostering a culture of innovation, technical excellence, and continuous learning.
• Manage multiple high-priority projects simultaneously while ensuring timely delivery and measurable business impact.
• Champion best practices in analytics, machine learning, experimentation, and data-driven decision-making across the organization.

Qualifications & Specifications

• Bachelor's or Masters degree in computer science, Statistics, Mathematics, Data Science, Engineering, or a related quantitative discipline. Advanced degree preferred.
• Minimum 8+ years of progressive experience in Data Science, with a strong track record of developing and deploying machine learning solutions that drive measurable business outcomes.
• Deep expertise in statistical modeling, machine learning, predictive analytics, customer analytics, and optimization techniques, with the ability to solve complex business problems at scale.
• Extensive hands-on experience building, deploying, monitoring, and maintaining machine learning models on cloud platforms, preferably Google Cloud Platform (GCP) and/or Microsoft Azure.
• Strong proficiency with cloud-native data and AI/ML services, including Databricks, Azure Machine Learning, Azure Data Factory, BigQuery, Vertex AI, and related cloud ecosystem tools.
• Experience designing scalable end-to-end data science solutions, including feature engineering, model training, validation, deployment, MLOps, and model performance monitoring.
• Advanced proficiency in Python, SQL, and modern data science frameworks and libraries for machine learning and analytics.
• Strong understanding of large-scale data processing, distributed computing, and cloud-based data architectures.
• Proven ability to translate business challenges into analytical solutions and deliver actionable insights through advanced modeling and experimentation.
• Exceptional data visualization, storytelling, and executive communication skills, with the ability to influence senior stakeholders and communicate complex analytical concepts to both technical and non-technical audiences.
• Demonstrated leadership experience mentoring data scientists, leading cross-functional initiatives, and driving adoption of data-driven decision-making across the organization.
• Strong analytical thinking, problem-solving capabilities, and a passion for innovation, continuous learning, and applying emerging AI/ML technologies to business challenges.