Senior Data Scientist

Keka Inc.; United Kingdom; On-site; GBP 90,000 - 130,000; Full time

Job summary

Keka Inc. is seeking a Senior Data Scientist to own optimization components for large-scale supply chain decision systems, including routing, scheduling, and resource allocation.

The role requires hands-on development of analytical and optimization models under a Data Science Lead, with strong business-data alignment and clear stakeholder communication. The ideal candidate will deliver scalable solutions by integrating ML and optimization, maintaining data workflows in Python/SQL, and working

Qualifications

• 8+ years in data science, OR/optimization or related field.
• Hands-on optimization (MILP, VRP, scheduling) and ML experience.
• Proficiency in Python and SQL.
• Experience with optimization solvers such as Gurobi.
• Familiarity with Azure and Databricks environments.
• Proven ability to translate business problems into data-driven solutions.
• Strong problem-solving and fast-paced collaboration skills.
• Effective communication with technical and business stakeholders.

Responsibilities

• Develop and enhance optimization models for routing, scheduling, and resource allocation.
• Apply ML techniques to support decision systems and bridge ML with optimization.
• Translate business requirements into structured analytical problems with constraints.
• Diagnose model issues and balance cost, service level, and feasibility trade-offs.
• Build data workflows using Python and SQL; deploy in Azure/Databricks.
• Ensure data quality and model reliability; support feedback loops.
• Collaborate with cross-functional teams and guide junior members.

Skills

Optimization

Machine Learning

Python

SQL

Gurobi

Azure

Databricks

Communication

Tools

Gurobi

Azure Databricks

Job description

We are seeking a Senior Data Scientist with strong expertise in optimization and applied machine learning to support the development of large-scale decision systems in supply chain operations, including routing, scheduling, and resource allocation.

This is a hands-on, execution-focused role working under the Data Science Lead. The successful candidate will own and enhance components of analytical and optimization models, ensuring they are scalable, reliable, and aligned with business needs. The role requires the ability to connect business requirements with data science solutions, operate in a fast-paced environment, and communicate effectively with both technical and non-technical stakeholders.

Key Responsibilities

• Develop and enhance optimization models using MILP and heuristic approaches, applying them to problems such as vehicle routing, scheduling, and resource allocation, and improving performance using solvers such as Gurobi
• Apply machine learning techniques to support decision systems, including predictive modeling, feature engineering, and generating inputs for optimization models, while ensuring strong integration between ML and optimization frameworks
• Translate business requirements into structured analytical and optimization problems, incorporating operational constraints and clearly communicating model assumptions, trade-offs, and outcomes to stakeholders
• Diagnose and resolve model issues including infeasibility, performance bottlenecks, and data inconsistencies, while analyzing trade-offs across cost, service level, and operational feasibility
• Develop and maintain data workflows using Python and SQL, and support scalable processing and deployment within cloud environments such as Azure and Databricks
• Ensure data quality and model reliability by validating inputs, identifying gaps, and supporting feedback loops to improve model accuracy and alignment with operations
• Collaborate with cross-functional teams, take ownership of model components, contribute to technical design discussions, and provide guidance to junior team members

Qualifications

• 8+ years of experience in data science, operations research, or a related field
• Strong hands-on experience in optimization (e.g., MILP, VRP, scheduling) and machine learning
• Proficiency in Python and SQL
• Experience working with optimization solvers such as Gurobi
• Familiarity with Azure and Databricks environments
• Proven ability to translate business problems into data-driven solutions
• Strong problem-solving skills and ability to work in fast-paced environments
• Effective communication skills with both technical and business stakeholders

Preferred Qualifications

• Experience in supply chain, logistics, or operations-focused environments
• Familiarity with large-scale optimization techniques or heuristic methods
• Experience working with distributed data systems or cloud-based analytics platforms
• What Success Looks Like
• You will deliver reliable and scalable model components that drive operational decisions, effectively bridge the gap between business and analytics, and contribute to measurable improvements in efficiency, service levels, or cost.

Why TechBlocks

Work directly with Fortune 500 executives and digital transformation leaders.

Be part of a fast-growing, AI-native software engineering firm redefining global delivery through our GCC-as-a-Service model.

Collaborate with global teams in Canada, the U.S., and India on cutting-edge cloud and AI initiatives.

Competitive compensation, performance incentives, and a culture that values ownership, agility, and innovation.