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

The RoleWe 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 daysCombine data engineering, modelling and lightweight application development to test ideas end-to-endConvert 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 weeksWork 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 quicklyHands-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 applicationsFamiliarity 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 daysYou can go from working PoC to useful prototype in 2-3 weeksYou unblock decisions by demonstrating feasibility quicklyYou focus on practical outcomes, not perfect code

Your ProfileEssential 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 SQLExperience with API Testing automationStrong experience with Data ScienceStrong 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.