Lead - Data Scientist

Job Title: Data Scientist - Lead

Company: FedEx

Location: Bangalore  

About FedEx:

FedEx is a global leader in logistics, offering a broad portfolio of transportation, e commerce, and business services. With a commitment to innovation and customer satisfaction, FedEx continually seeks to optimize its operations and enhance the customer experience.  

Role Overview

We are seeking an experienced and highly motivated Lead Data Scientist to join our Customer Analytics team. This role requires a strong blend of advanced analytics expertise, business acumen, leadership, and stakeholder management skills. The ideal candidate will lead the development of data-driven solutions that enhance customer understanding, predict future behavior, personalize customer experiences, and drive business growth. This role will play a critical part in optimizing the customer lifecycle through advanced analytics, machine learning, and actionable business insights. 

Key Responsibilities

Customer Analytics & Insights: 

• Analyze customer interactions across multiple touchpoints to uncover behavioral patterns, trends, and growth opportunities. 
• Develop customer segmentation frameworks based on behavioral, demographic, transactional, and engagement data to enable targeted business and marketing strategies. 
• Generate actionable insights that support customer acquisition, retention, loyalty, upsell, and cross-sell initiatives. 
• Develop and enhance Churn, X-sell/ Up-sell, Customer Lifetime Value (CLTV) models to assess long-term customer value and inform retention and investment strategies

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.  

Cloud, Data Engineering & Model Operationalization:

• Develop, deploy, and monitor machine learning solutions on Azure and/or GCP cloud platforms. 
• Build and optimize scalable data pipelines using Azure Data Factory and related technologies for automated data ingestion, transformation, and analytics workflows. 
• Partner closely with Data Engineering, MLOps, and Analytics teams to operationalize and scale advanced analytical solutions in production environments. 

Business Partnership & Strategic Leadership:

• Collaborate with Marketing, Sales, Commercial, Product, and Analytics teams to align analytical initiatives with business objectives.
• Translate complex analytical findings into clear, compelling business recommendations through effective storytelling and executive-level communication. 
• Provide expert consultation and strategic guidance to senior leadership on customer analytics, growth opportunities, and performance optimization.
• Contextualize business performance metrics and trends to uncover risks, opportunities, and strategic actions. 

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. 

Preferred Qualifications:

• Bachelor's or Master's 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.

Join our team: 

Are you a data-driven problem solver passionate about customer behavior Join our team to build advanced analytics solutions, leveraging cloud technologies to optimize marketing and sales strategies and enhance every customer experience/ interaction.