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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 grow your career in tech.
- Why this job: Join a fast-paced environment where your ideas can quickly become reality.
- Qualifications: Proficiency in Python, SQL, and experience with data science and machine learning.
The predicted salary is between 50000 - 65000 ÂŁ 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 Slough 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 Slough
✨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 Python and SQL prowess. Maybe even include a link to a GitHub repo where we can see your projects in action. We love seeing practical applications of your knowledge!
✨Tip Number 3
Network like a pro! Connect with folks in the data engineering and machine learning space on LinkedIn or at local meetups. You never know who might have the inside scoop on opportunities or be able to refer you directly to us at StudySmarter.
✨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. Don’t forget to tailor your application to highlight your experience with rapid prototyping and data-driven decision-making.
We think you need these skills to ace Prototyping Engineer (Data Engineering, Data Science and Machine Learning) in Slough
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 can take an idea and turn it into something tangible quickly, so share specific examples of your past work!
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 skills and experiences that relate to the role.
Tailor Your Application: Don’t just send a generic application! We love it when candidates tailor their applications to our job description. Highlight your relevant skills in data engineering, machine learning, and rapid prototyping to catch our eye.
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’s super easy!
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.
✨Showcase Your Technical Skills
Brush up on your Python and SQL skills, as these are crucial for the role. Prepare to discuss any projects where you've used these languages for data processing or machine learning. If you have experience with APIs or cloud data platforms like Snowflake, be sure to mention that too!
✨Emphasise Independent Problem-Solving
This role requires a lot of autonomy, so be prepared to share examples of when you've worked independently to solve complex problems. Discuss how you approach ambiguous situations and how you prioritise practical outcomes over perfect code.
✨Communicate Clearly and Confidently
Since you'll need to communicate results clearly, practice explaining your ideas and solutions in a straightforward manner. Use visuals or examples if possible, and be ready to answer questions about your thought process and decision-making.