Marketing Data Scientist

Get AI-powered advice on this job and more exclusive features. One of The Sage Group’s clients, a leading multinational manufacturer and marketer of consumer and professional products, is looking for a Marketing Data Scientist to primarily focus on building self-service tools around marketing mix modeling. In this role, you will: As a Data Scientist in Marketing, you will have the opportunity to apply data science techniques across our portfolio of brands to develop novel tools and analyses that push the boundaries of marketing analytics within the company. You will support building data products and translating data into clear and compelling insights ensuring proper activation that leads to business impact. You’ll work closely with other data scientists, engineers and business partners across Marketing, Sales and R&D to derive insights from diverse data sources, help the business make data-driven decisions and apply cutting edge data science techniques. The ideal candidate is curious, collaborative, and passionate about data science and product analytics with business facing experience. Key Responsibilities: Contribute to the development and deployment of end-to-end AI/ML/Gen AI models, focusing on marketing, measurement, and predictive analytics. Explore, test and implement GenAI solutions (e.g., LLMs, embeddings, RAG pipelines) for use cases like personalized marketing, customer insights, or content generation. Scope and define data science projects, set clear deliverables, and collaborate with stakeholders to develop and deploy impactful models. Write clean, well-organized code in GitHub repositories , following version control and collaboration best practices for development with other members of the team Collaborate closely with data engineers to ensure data quality, feature engineering, and the development of efficient data pipelines. Act as a strategic partner to business stakeholders, helping them frame problems in a data-driven way and translating business goals into analytical solutions. Lead discovery sessions with marketing, product, and leadership teams to understand pain points and identify opportunities where data science can create value. Present analytical findings and model results through compelling storytelling, using visualizations and business context to drive alignment and decision-making. Education & Experience: Bachelor’s degree or higher in data science, math, statistics, computer science or other relevant quantitative fields. 1+ years of relevant experience with a master’s, or 2–3+ years with a bachelor’s Highly collaborative and able to communicate effectively with non-technical audiences. Business partner facing experience is preferred. Technical Skills: Proficient in Python, SQL, and other open-source tools, including Generative AI frameworks and other relevant technologies. Experience in predictive modeling, machine learning, and Generative AI tools, with the ability to develop production-ready AI/ML models and can write clean, well-organized code in GitHub repositories. Consumer goods (CPG/FMCG) experience preferred. Comfortable working with unstructured and messy data, including data exploration, cleaning, and transformation to extract meaningful insights. Experience with cloud-based data tools like BigQuery, Azure Synapse and GCS is a plus Experience with Docker, Cloud deployments and product building is a plus Curious self-starter who can think creatively and look for & help develop elegant and viable solutions for real world problems. Skilled at producing actionable and compelling recommendations driven by complex data. Strong leadership and communication skills, with an ability to share ideas clearly with different audiences. Excellent time and project management skills; able to work efficiently under tight deadlines. Collaborative team player with good interpersonal skills and a willingness to build strong working relationships. Strong business acumen & interest in understanding the business and applying data science to real-world consumer or marketing challenges. Comfortable working in a dynamic environment and able to identify needs, develop a plan of action and implement. Open to learning new tools, methods, and approaches as needed. Seniority level

Mid-Senior level Employment type

Full-time Job function

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