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- Tasks: Deliver a proof of concept using static datasets and focus on data preparation and anomaly detection.
- Company: Join a forward-thinking team that values innovation and collaboration.
- Benefits: Remote work, competitive pay, and potential for contract extension.
- Why this job: Make a real impact by crafting interpretable features and communicating findings to stakeholders.
- Qualifications: Strong Python skills and experience in feature engineering and anomaly detection.
- Other info: Opportunity to work in a dynamic environment with potential for future projects.
The predicted salary is between 50000 - 70000 £ per year.
Duration: 5 weeks (with potential for extension)
Status: Outside IR35
Location: Remote (UK-based)
Start Date: ASAP
About the Role
We are seeking an experienced Data & ML Contractor to deliver a proof of concept using static, structured datasets. This is a focused, pragmatic engagement centred on data preparation, feature engineering, and anomaly detection - with an emphasis on clear, interpretable outputs for stakeholders. This is not a heavy Data Engineering or MLOps engagement. There is no requirement for live pipelines, streaming ingestion, or ongoing automated refresh. The successful candidate will work hands-on to profile data, engineer meaningful features, develop detection logic, and communicate findings effectively to non-technical stakeholders.
Essential Skills & Experience
- Strong Python for data processing and analytics (e.g., pandas, numpy; scikit-learn or equivalent)
- Structured data expertise: joins, aggregations, data cleaning, handling missing data/outliers, basic data modelling concepts
- Feature engineering: ability to craft interpretable, business-relevant features
- Anomaly detection experience: practical knowledge of rule-based and statistical methods; ML-based approaches where appropriate
- Requirements & communication: ability to work with stakeholders, define success criteria, and explain outputs clearly
Desirable (Nice to Have)
- Power BI / BI visualisation (or similar) to support validation and stakeholder-facing outputs
- Familiarity with Azure for accessing datasets or sharing PoC artefacts (basic storage/compute)
- Ability to outline what would be needed to scale the PoC toward production later (without implementing full MLOps now)
Senior Machine Learning Engineer employer: Total Recruitment Group
Contact Detail:
Total Recruitment Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the machine learning field and let them know you're on the lookout for opportunities. Sometimes, a friendly nudge can lead to a hidden gem of a job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects, especially those involving data preparation and anomaly detection. This will give potential employers a taste of what you can do and how you communicate your findings.
✨Tip Number 3
Prepare for interviews by brushing up on your Python skills and understanding feature engineering concepts. Be ready to discuss how you've tackled similar challenges in the past and how you can deliver clear outputs for stakeholders.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are proactive and engaged. Plus, it makes it easier for us to keep track of your application and get back to you quickly.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, data processing, and feature engineering. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for this contract. Mention your experience with anomaly detection and how you can communicate findings to non-technical stakeholders.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled data challenges in the past. We love seeing practical knowledge, especially when it comes to crafting interpretable features and handling outliers.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves.
How to prepare for a job interview at Total Recruitment Group
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills, especially with libraries like pandas and scikit-learn. Be ready to discuss how you've used these tools in past projects, particularly around data processing and feature engineering.
✨Prepare for Practical Scenarios
Since the role focuses on anomaly detection and feature engineering, think of specific examples where you've tackled these challenges. Be prepared to explain your thought process and the impact of your work on stakeholders.
✨Communicate Clearly
You’ll need to explain complex concepts to non-technical stakeholders, so practice simplifying your explanations. Use analogies or visual aids if necessary, and be ready to discuss how you define success criteria in your projects.
✨Showcase Your Problem-Solving Skills
Think about how you would approach the proof of concept outlined in the job description. Be ready to discuss how you would profile data, handle missing values, and develop detection logic, while keeping the outputs interpretable for the business.
