Prototyping Engineer (Data Engineering, Data Science and Machine Learning)

Prototyping Engineer (Data Engineering, Data Science and Machine Learning) Whitehall Resources are looking for a Prototyping Engineer (Data Engineering, Data Science and Machine Learning). This role is based onsite in London for an initial 6 month contract. • • • Inside IR35 • • • The Role We are looking for a highly autonomous contractor who can take ideas and concepts, think independently, and return within a few days with a working proof of concept. This role is focused on rapid experimentation and validation, not long development cycles. The goal is to quickly assess whether ideas are viable and worth scaling. • Your responsibilities:Build PoCs - Take loosely defined problems and turn them into proofs of concepts (PoCs) within days • Combine data engineering, modelling and lightweight application development to test ideas end-to-end • Convert PoCs to working Prototypes - Where a POC shows promise, there would be additional effort to grow it into a prototype (applying the concept to functional business needs) within 2-3 weeks • Work independently with minimal guidance and iterate quickly based on feedback and communicate results clearly. • What we are looking for:Strong ability to translate ideas into working solutions quickly • Hands-on skills across: • Python (data processing, ML, prototyping). • Data engineering (APIs, data pipelines, SQL, cloud data). • Lightweight app development (APIs, simple frontends, notebooks, dashboards). • Solid (not necessarily extensive) knowledge on the statistical/mathematical fundamentals that support and proposed ML methodologies. • Experience building end-to-end prototypes, not just models. • Comfortable working in ambiguous, fast-moving environments. • Strong problem-solving and independent thinking. • Nice to have:Experience integrating LLMs or AI services into applications • Familiarity with modern data platforms (e.g. Snowflake) • Experience with visualisation tools (e.g. Tableau, Plotly) • Working knowledge of marketing and advertising • What success looks like:You can go from idea → working PoC in 2–3 days • You can go from working PoC to useful prototype in 2-3 weeks • You unblock decisions by demonstrating feasibility quickly • You focus on practical outcomes, not perfect code Your Profile • Essential skills/knowledge/experience:Strong hands‑on experience in Analytics & Reporting, with the ability to translate business requirements into measurable insights and KPIs. • Advanced proficiency in SQL and Python for data extraction, transformation, analysis, and automation of analytical workflows. • Solid foundation in Data Science and Machine Learning, including feature engineering, model development, evaluation, and performance monitoring. • Practical experience with NLP techniques using scikit‑learn, applying text analytics to derive insights from unstructured data. • Proven ability in API testing and automation, ensuring data quality, reliability, and stability of data/ML services. • Excellent analytical and problem‑solving skills, with experience working closely with business stakeholders; exposure to Snowflake, Tableau, or Campaign Marketing analytics is an added advantage. • Desirable skills/knowledge/experience:Strong experience in Advanced SQL • Experience with API Testing automation • Strong experience with Data Science • Strong experience with Machine Learning, NLP Technologies with scikit-learn etc. • Strong hands-on experience with Python (data processing, ML, prototyping) • Strong hands-on experience with Data engineering (APIs, data pipelines, SQL, cloud data). • Lightweight app development (APIs, simple frontends, notebooks, dashboards) • Solid (not necessarily extensive) knowledge on the statistical/mathematical fundamentals that support and proposed ML methodologies. • Experience with cloud data platforms (e.g., Snowflake) and modern data warehousing concepts for scalable analytics and ML workloads. • Exposure to data visualization tools such as Tableau or similar BI platforms for creating executive‑level dashboards and self‑service reporting. • Experience working in Agile delivery models and collaborating cross‑functionally with business, analytics, and engineering teams. • Working knowledge of campaign marketing analytics, including customer segmentation, attribution, churn, and uplift analysis is beneficial.