Our client is a global management consulting firm specializing in delivering practical results and strategic insights for leading businesses across the world. With over 2,200 professionals and a legacy of over 35 years, our client combines deep industry expertise with rigorous analysis to support clients in achieving transformative outcomes.
Job Summary
The Data & Analytics (D&A) team is seeking a contract Data Scientist to support high-impact client engagements. This role involves solving complex business problems using data science techniques, building scalable machine learning solutions, and contributing to the development of analytical applications. The ideal candidate is a hands-on technical expert with strong experience in ML/AI, model deployment, and collaboration across cross-functional teams.
Key Responsibilities
Client Engagement & Delivery
Lead end-to-end data science projects from ideation to deployment, focusing on solving commercial problems across multiple clients.
Build and deploy advanced ML models in cloud environments (AWS, Azure, GCP), ensuring scalability, performance, and reliability.
Collaborate with clients to integrate analytical insights into business workflows and guide data-driven decision-making.
Execute a range of analytics tasks including data aggregation, cleaning, manipulation, predictive modeling, geospatial analysis, NLP, and GenAI.
Analytical Tools & Product Innovation
Develop state-of-the-art analytical applications using modern machine learning algorithms.
Contribute technical thought leadership in designing tools, services, and proprietary data products.
Ensure development follows best practices in data integrity, scalability, and maintainability.
Business Development & Upskilling
Support Managing Directors with proposal development when analytics is critical to scope.
Provide training and capability overviews to business leaders to help commercialize the D&A offering.
Capability Development
Stay current with emerging tools, frameworks, and best practices in data science and analytics.
Contribute to the technical roadmap and mentor team members across projects and tools.
Enhance and evangelize MLOps best practices (CI/CD, model monitoring, performance tracking).
Requirements
Education & Experience
Degree in a quantitative field such as Statistics, Data Science, Computer Science, Mathematics, Engineering, or Economics.
Minimum 2 years of hands-on experience in applied data science (4+ years for senior-level candidates).
Technical Skills
Proficiency in Python (with ML libraries like scikit-learn, TensorFlow, PyTorch), SQL, Spark.