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For Companies At a Glance
- Tasks: Create rapid prototypes and proofs of concept for innovative data solutions.
- Company: Dynamic tech firm in London focused on data engineering and machine learning.
- Benefits: Competitive pay, flexible working, and opportunities for skill development.
- Other info: Great chance to work independently and make a real impact in tech.
- Why this job: Join a fast-paced environment where your ideas can quickly become reality.
- Qualifications: Strong skills in Python, SQL, and data engineering; experience with ML is a plus.
The predicted salary is between 50000 - 60000 £ per year.
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.
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).
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.
Prototyping Engineer (Data Engineering, Data Science and Machine Learning) in London employer: Whitehall Resources
Contact Detail:
Whitehall Resources Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Prototyping Engineer (Data Engineering, Data Science and Machine Learning) in London
✨Tip Number 1
Get your hands dirty with some quick prototypes! When you’re applying for the Prototyping Engineer role, show us how you can turn ideas into working proofs of concept in just a few days. Share examples of your past work that highlight your ability to iterate quickly and deliver results.
✨Tip Number 2
Don’t just talk about your skills; demonstrate them! Use your application to showcase your hands-on experience with Python, SQL, and data engineering. We want to see how you’ve tackled real-world problems and turned them into effective solutions.
✨Tip Number 3
Be ready to discuss your thought process! During interviews, we’ll want to know how you approach ambiguous problems and what steps you take to validate your ideas. Prepare to share specific examples where you’ve successfully navigated uncertainty.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows us you’re serious about joining our team and ready to dive into the exciting world of data engineering and machine learning.
We think you need these skills to ace Prototyping Engineer (Data Engineering, Data Science and Machine Learning) in London
Some tips for your application 🫡
Show Your Prototyping Skills: Make sure to highlight your experience in building proofs of concept and prototypes. We want to see how you've taken ideas and turned them into working solutions quickly, so share specific examples that demonstrate your hands-on skills.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon and get straight to the point about your relevant experience and skills. This will help us understand your fit for the role faster.
Tailor Your Application: Don’t just send a generic application! Tailor your CV and cover letter to reflect the specific requirements of the Prototyping Engineer role. We love seeing how your unique background aligns with our needs, so make it personal!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it makes the process smoother for everyone involved!
How to prepare for a job interview at Whitehall Resources
✨Know Your PoCs Inside Out
Before the interview, make sure you can discuss your past experiences with proofs of concept (PoCs) in detail. Be ready to explain how you took a loosely defined problem and turned it into a working solution quickly. Highlight specific examples where you demonstrated your ability to iterate based on feedback.
✨Brush Up on Your Tech Skills
Since this role requires strong hands-on skills in Python, SQL, and data engineering, ensure you're comfortable discussing these technologies. Prepare to talk about your experience with APIs, data pipelines, and any lightweight app development you've done. Being able to showcase your technical prowess will definitely impress.
✨Showcase Your Problem-Solving Mindset
This position values independent thinking and quick decision-making. Think of scenarios where you faced ambiguous challenges and how you approached them. Be prepared to share how you prioritised practical outcomes over perfect code, as this aligns with the company's focus on rapid experimentation.
✨Communicate Clearly and Confidently
Effective communication is key, especially when discussing complex ideas. Practice explaining your projects and results in a clear and concise manner. Use visuals or examples if possible, as this can help convey your points better and demonstrate your familiarity with data visualisation tools like Tableau.