Engagement Manager Data Science

Leadership and Strategic Oversight.
Lead, mentor, and manage a team of data scientists, analysts, and other data professionals.
Set clear goals and provide guidance on projects..
Develop and execute the data science strategy aligned with business objectives in the retail and CPG Clients..
Work closely with senior leadership, marketing, operations, sales, and IT teams to ensure data science initiatives are integrated and deliver business value..
Communicate insights and findings to C-level executives and business leaders in a clear and actionable manner.
Influence decision-making through data-driven insights..
Identify skills gaps and nurture talent within the team.
Provide opportunities for team members to grow and stay updated with the latest data science technologies..
Data Science and Machine Learning Models.
Spearheaded design and development of advanced machine learning models to drive key business functions such as demand forecasting, pricing optimization, inventory management, customer segmentation, and personalized marketing..
Work with large and complex datasets, including structured, semi-structured, and unstructured data, to uncover insights.
This may include transactional data, customer feedback, social media data, and IoT data from retail environments..
Apply statistical techniques (e.g., time series analysis, regression analysis, clustering, deep learning) to solve complex business problems and deliver actionable insights..
Lead the creation of optimization algorithms for supply chain management, product assortment, promotions, and pricing strategies to improve margins and sales..
Identify opportunities for automating processes and reports using machine learning and AI to improve efficiency and decision-making.
Business Insights and Problem Solving.
Leverage deep knowledge of the retail and CPG to solve industry-specific problems, such as customer lifetime value, trade promotion analysis, category management, and demand sensing extra..
Analyze customer behavior, market trends, and competitor actions to generate actionable insights that support strategic business decisions..
Help guide the business with data-backed insights on product launches, pricing strategies, marketing campaigns, and supply chain improvements..
Innovation and Continuous Learning.
Stay ahead of emerging trends in data science, AI, and analytics to ensure the organization remains competitive..
Implement industry best practices in analytics, ensuring the highest standards of data security, model governance, and performance monitoring..
Lead pilot projects to test new methodologies or technologies that can bring innovative solutions to business challenges..
Change Management and Process Improvement.
Identify opportunities for process improvements within the data science team and across the organization to enhance operational efficiency..
Effectively manage and implement change within the organization as new data science initiatives are rolled out..
Required Skills and Qualifications.
10+ years of experience in data science, with significant experience in the retail/CPG firms..
Expertise in machine learning, AI, deep learning, and statistical modelling techniques..
Proficiency in Python, R, SQL, and machine learning libraries like Scikit-learn, TensorFlow, PyTorch, etc..
Experience working with cloud platforms (AWS, Google Cloud, Azure) and big data tools like Hadoop and Spark..
Ability to translate complex data insights into clear, actionable business recommendations..