senior staff data scientist [up to 30k].

• lead, mentor, and upskill a team of data scientists and analysts; set best practices and standards in modelling, experimentation, and MLOps.
• collborate with product and engineering leadership to define the long-term roadmap and ensure alignment with business goals.
• design, architect, build and deploy large-scale segmentation systems across multiple levels of granularity.
• develop and optimize advanced clustering, classification, and representation-learning models using statistical and machine learning techniques.
• integrate and operationalize large, complex datasets—including census, geospatial, demographic, and unstructured data—to enrich segmentation workflows.
• build robust model pipelines in distributed environments (PySpark, Databricks) and ensure scalability, reproducibility, and reliability.

knowledge, skills and experience

• 8–12+ years of experience in data science with at least 3–4 years in a senior or lead role shaping analytical strategy or leading teams.
• expertise in segmentation systems, including unsupervised learning (K-Means, clustering), dimensionality reduction (PCA, Factor Analysis), and ML models (GLM, tree-based models, boosting).
• proficient in Python, SQL, and R, with advanced hands-on experience in distributed data processing using PySpark, Databricks, or similar platforms.
• ability to work with diverse first-party, third-party, and large-scale demographic datasets (e.g., Census data, area-level data, unstructured sources).
• experience in MLOps, feature stores, or production ML pipeline design.
• background in geospatial modelling, representation learning, or scalable personalization engines.
• expertise in data visualization using Tableau, Looker, Alteryx, or libraries like D3.js.