Lead Data Scientist

About The Job You Are Considering

Your Role

Technical Leadership & Strategy

• Lead and mentor a multidisciplinary team of data scientists, ML engineers, and analysts.
• Define and implement data science best practices, modeling standards, and technical roadmaps.
• Collaborate with business and technology leaders to identify and prioritize AI/ML opportunities.
• Review and validate modeling approaches, code quality, and solution architectures.

Advanced Analytics & Ai Development

• Design and build scalable machine learning, deep learning, and statistical models.
• Lead projects in NLP, LLMs, computer vision, recommendation systems, and predictive analytics.
• Own the full model lifecycle: experimentation, feature engineering, model selection, tuning, deployment, and monitoring.

Data Engineering & Deployment

• Partner with data engineers to develop robust, scalable data pipelines.
• Ensure seamless deployment using CI/CD, MLOps, and automation frameworks.
• Monitor model performance and implement retraining workflows to maintain accuracy.

Business Partnership & Solutioning

• Translate business problems into actionable analytical solutions.
• Present insights and recommendations to both technical and non-technical stakeholders.
• Align AI/ML solutions with business KPIs and measurable outcomes.

Governance, Quality & Innovation

• Champion responsible AI practices, model governance, explainability, and compliance.
• Drive innovation by experimenting with new algorithms, tools, and frameworks.
• Contribute to knowledge sharing and reusable solution components.

Technical Skills

• Expertise in Python (Pandas, NumPy, Scikit-learn), deep learning frameworks (TensorFlow, PyTorch).
• Strong knowledge of ML algorithms, statistics, and experimental design.
• Hands-on experience with NLP, LLMs, computer vision, or advanced modeling.
• Proficiency in SQL and big data tools (Spark, Databricks, Hadoop).
• Experience with cloud platforms (AWS, Azure, GCP) and ML services.
• Familiarity with APIs, model serving, and MLOps tools (MLflow, Kubeflow, Docker, Kubernetes).

Professional Experience

• Proven track record in data science, ML, or advanced analytics.
• Experience leading teams and delivering production-grade models.
• Agile/DevOps experience is a plus.

Soft Skills

• Excellent communication and storytelling abilities.
• Strong leadership, mentoring, and decision-making skills.
• Ability to translate complex technical concepts into business value.
• Strategic thinker with a problem-solving mindset.

Preferred Qualifications

• Master’s or PhD in Data Science, Computer Science, Statistics, or related fields.
• Experience with GenAI, LLM fine-tuning, vector databases, RAG pipelines.
• Relevant certifications (Data Scientist, ML Engineer, Cloud).
• Domain expertise in BFSI, healthcare, retail, manufacturing, or SaaS.
• Why you should consider Capgemini
• Growing clients’ businesses while building a more sustainable, more inclusive future is a tough ask.
• When you join Capgemini, you’ll join a thriving company and become part of a diverse collective of free-thinkers, entrepreneurs and industry experts.
• We find new ways technology can help us reimagine what’s possible.
• It’s why, together, we seek out opportunities that will transform the world’s leading businesses, and it’s how you’ll gain the experiences and connections you need to shape your future.
• By learning from each other every day, sharing knowledge, and always pushing yourself to do better, you’ll build the skills you want.
• You’ll use your skills to help our clients leverage technology to innovate and grow their business.
• So, it might not always be easy, but making the world a better place rarely is.

About Capgemini

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