Data Science Manager

Senior Associate, Data Science

Role Summary:

In this role, you will help to drive the Data & AI practice by playing a critical role in delivering solutions for our clients and contributing to business development activities. This is a hands-on role where you will apply advanced techniques for data analytics, machine learning, and AI as a core building block for our services.

You will leverage your experience across industries to understand business requirements, identify approaches and designs, and work with multi-disciplinary teams to develop solutions.

As an evangelist for Analytics, you will engage with broader data, engineering, product, and strategy practices to provide insights into best practices and emerging technologies and techniques, ensuring that the solutions we develop are data and insight-driven.

Key Responsibilities:

• You will consult with clients to explore and define business problems and advise on how to apply data analytics, business intelligence, and machine learning to solve them.
• You will employ advanced analytics and statistical methods to prepare and analyze data for (predictive) modelling, from prototypes to production.
• Bring expertise in key areas such as customer intelligence (segmentation, behavior analysis, personalization, recommender systems, forecasting).
• You will build comprehensive reporting and intelligence solutions for business users and management to leverage data-driven insights for decision making.
• You will help us establish standards in statistical analysis, AI, machine learning, and data visualization to ensure consistency across projects and teams, as well as prepare reports and presentations for relevant stakeholders (client side & internal).
• You will support business development activities in contributing to proposals and demonstrations

Must-Have:

• Five years of relevant professional experience working as a data scientist.
• A passion for using AI and data for business transformation and a thirst to continually learn and keep pace with the latest innovations and applications.
• Experience in statistical methods and modelling techniques (e.g., Random Forests, Clustering, Linear Regression).
• Experience using and integrating generative AI models and platforms, agentic solutions, and context engineering techniques.
• Experience with programming languages (Python, R, SQL) and AI/ML platforms (e.g. Databricks, and cloud platforms (e.g. Azure Synapse, AWS SageMaker, Google Cloud Vertex AI).
• Experience with data science, data visualization, and data analysis tools (e.g., scikit-learn, pandas and NumPy, Apache Spark, matplotlib, ggplot2).
• Experience working with large volume data sets and multiple data formats and interfaces (SQL, JSON, REST, Parquet, streaming, geospatial, unstructured).
• Technical knowledge of data visualization tools (Tableau & Power BI), graphing and chart libraries (e.g., matplotlib, plotly).
• Experience working in a client-facing (ideally) consulting role, having great written and verbal communication skills, and the ability to work closely with stakeholders, or having been part of a project team.
• Flexibility and the willingness to travel are required for this role, as you might need to spend time on-site with our clients.
• Experience in agile methodologies and relevant tools (Confluence, Jira, git).
• Experience working in cross-cultural and cross-disciplinary teams.

Nice-to-Have:

• Understanding of data (management) platforms (CDP, CRM, DMP, Big Data Lakes, Cloud) and tools (ETL, Processing, marketing automation, etc.).
• Experience in production environments for Machine Learning products, knowledge of the tools that are needed for model deployment and lifecycle management in ML engineering (Docker, Kubernetes).
• Solid knowledge of software engineering principles & deployment methods (preferably in cloud environments).
• Experience in data-driven marketing, campaign development, measurement, and optimization, Martech, CDP, etc.
• Industry experience in the Finance, Automotive, Logistics, Energy, or public sector.