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Collinson Logo Collinson · IT - Software Development

Head of Data Science

India, Mumbai · Job Posted March 21, 2026
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Job Description

The Head of Data Science is a senior position responsible for shaping, operationalizing, and advancing the organization’s data science strategy. This role focuses on creating high-value, data-driven insights and solutions that drive innovation, improve decision-making, and deliver measurable business outcomes. You will act as the bridge between business strategy and advanced analytics execution, ensuring that data science becomes a central enabler of enterprise growth, customer engagement, and operational excellence.

Job Responsibility

  • Establish and lead a high-performing Data Science function, fostering an environment of innovation, experimentation, and analytical excellence
  • Own the organizational data science strategy, including defining and delivering the intelligent data products vision and roadmap
  • Drive the full lifecycle of data science projects, from problem framing and data exploration to model development, validation, deployment, and scaling
  • Partner with senior leaders across platform, product, and business units to refine and execute the organizational data science strategy, ensuring alignment with business goals
  • Collaborate with stakeholders to identify high-impact use cases and prioritize initiatives that deliver measurable business value
  • Deliver advanced analytics and machine learning solutions addressing challenges such as customer personalisation, operational optimisation, fraud detection, predictive forecasting and more
  • Manage and mentor a team of data scientists, developing their technical and business skills while aligning their efforts with organizational priorities
  • Oversee the integration of data science solutions into existing systems, ensuring robustness, scalability, and long-term performance
  • Promote innovation by exploring new data science applications beyond current ecosystem limitations
  • Champion best practices in data governance, ethical data standards, and regulatory compliance
  • Stay ahead of emerging trends in data science, analytics, and AI to introduce innovations that reinforce the organization’s market leadership
  • Lead the adoption of robust experimentation and causal inference methods (A/B testing, uplift testing) to embed an evidence-based culture across the business
  • Partner closely with Data Engineering and Platform teams to ensure high-quality pipelines, reliable feature stores, and scalable production deployments
  • Drive the operationalization of predictive models in areas such as demand forecasting, customer lifetime value, churn prediction, and fraud detection
  • Champion the use of advanced analytics for decision support, ensuring insights are actionable, timely, and embedded into business processes
  • Ensure all initiatives deliver measurable commercial ROI, linking data science outcomes to customer loyalty, revenue growth, and cost optimization

Requirements

  • Proven track record in leading data science projects with measurable business outcomes in a commercial setting
  • Expertise in statistical modelling, machine learning, predictive analytics, and data-driven decision-making
  • Strong experience with data science tools, frameworks, and cloud platforms
  • Proficiency in designing and managing end-to-end data science workflows, including data preparation, model training, deployment, and monitoring
  • Leadership experience managing teams of data scientists or analysts in fast-paced, innovation-driven environments
  • Ability to engage with C-suite stakeholders, translate business needs into analytical solutions, and communicate results effectively
  • Deep understanding of data ethics, privacy, and governance frameworks
  • Proven expertise in applied machine learning, predictive modelling, and statistical analysis within large, complex organizations
  • Strong track record of deploying and maintaining models in production, with emphasis on scalability, monitoring, and lifecycle management
  • Experience designing and leading experimentation frameworks to validate business impact
  • Proficiency in working with modern data architectures (e.g., lakehouse, feature stores, streaming systems) to enable real-time analytics and ML
  • Commercial acumen with the ability to translate analytical outputs into tangible business outcomes

Nice to have

  • Self-motivator with a desire to learn new skills and embrace new technologies in a constantly changing technology landscape
  • Ability to thrive in a fast moving environment
  • Ability to show initiative, innovation and work independently when required
  • Ability to work at pace and tackle project challenges in a collegiate, collaborative way
  • Goal and outcome orientated
  • Thoroughness and attention to detail
  • Good communication skills (ability to present, inform and guide others)
  • Ability to bridge communications between technical and business focussed groups
  • Comfortable working with people at all levels in an organisation
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