At a Glance
- Tasks: Build and validate ML models for live investment strategies in a dynamic hedge fund environment.
- Company: Join a leading systematic hedge fund with a focus on innovation and collaboration.
- Benefits: Competitive daily rate, flexible contract, and the chance to work with top-tier professionals.
- Other info: Exciting opportunity to work directly with quant researchers and advance your career.
- Why this job: Make a real impact on financial markets using cutting-edge machine learning techniques.
- Qualifications: 4+ years of ML engineering experience in a hedge fund or quant asset management setting.
A systematic hedge fund is seeking a Machine Learning Engineer to work embedded within their quant research team - building, validating and productionising ML models for alpha signal generation, regime classification and factor research across equities and futures. This is not a generic ML engineering role. You will be working directly alongside quant researchers on models that feed live investment strategies.
Candidates must have machine learning engineering experience gained within a systematic hedge fund, quant asset manager, or prop desk - specifically within a research function where ML models are used in the investment process. ML engineering experience from tech, retail, or enterprise environments is not sufficient. If you have not previously built or productionised ML models that feed into live trading strategies or systematic investment decisions, this role is not the right fit.
What they need:
- 4+ years ML engineering within a systematic hedge fund, quant asset manager, or prop desk - building models used in live trading or investment research
- Deep understanding of challenges specific to financial ML: non-stationarity, lookahead bias, overfitting, regime changes, and transaction cost modelling
- Strong Python — PyTorch or TensorFlow, scikit-learn, feature engineering pipelines
- Experience with time-series ML methods applied to financial data - returns prediction, signal construction, regime detection
- ML flow or equivalent for experiment tracking and model versioning in a research context
- Familiarity with alternative data sources (NLP, pricing microstructure, cross-asset signals) beneficial
- KDB+/q or Pandas/Polars for financial time-series data handling
6–9 months. DM or apply via our site. REF: C016
ML Engineer | Alpha Research & Signal Generation | £900–£1,100/day | Contract | London employer: Platinum & Partners
As a leading systematic hedge fund located in London, we pride ourselves on fostering a dynamic and innovative work culture that empowers our Machine Learning Engineers to collaborate closely with quant researchers. Our commitment to employee growth is evident through continuous learning opportunities and the chance to work on cutting-edge ML models that directly influence live investment strategies. With competitive daily rates and a focus on impactful work, we offer an exceptional environment for those looking to make a meaningful contribution in the financial sector.
StudySmarter Expert Advice🤫
We think this is how you could land ML Engineer | Alpha Research & Signal Generation | £900–£1,100/day | Contract | London
✨Showcase Your Skills with a Public Portfolio
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✨Leverage Local Networking Opportunities
Keep an eye out for local data science meetups or tech events in your area. These are golden opportunities to meet potential clients and collaborators face-to-face. Plus, who doesn't love a bit of networking over pizza and drinks?
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We think you need these skills to ace ML Engineer | Alpha Research & Signal Generation | £900–£1,100/day | Contract | London
Some tips for your application 🫡
Showcase Your Projects:When applying for a freelance data science role like ML Engineer | Alpha Research & Signal Generation | £900–£1,100/day | Contract | London at Platinum & Partners, it’s crucial to highlight your projects. Include a portfolio that features at least two or three projects involving data analysis, machine learning, or visualisation. Make sure to describe the tools and methodologies you used, so we can see your skills in action!
Quantify Your Achievements:Freelance gigs, especially in data science, often ask for proven results. In your CV, include any relevant metrics or outcomes from your previous work. Did your analysis help reduce costs by a certain percentage? Or did your predictive model improve performance? Numbers speak volumes!
Introduce Your Style:Since freelancing is all about your individual style and approach, use your cover letter to share how you tackle data problems. This is your chance to let us know how you think, your creative problem-solving methods, and how you would approach a project at Platinum & Partners.
Be Real About Your Rates:When you send in your application, don’t forget to mention your freelance rates and availability. We appreciate clarity up front, and it helps us gauge if you fit within our budget and timeline. Being transparent in this aspect shows professionalism and readiness!
How to prepare for a job interview at Platinum & Partners
✨Show Off Your Data Wizardry
As a freelancer in data science, you'll want to present a portfolio that showcases your best projects. We should pull together examples where you tackled real problems with data analytics, machine learning models, or visualisations. It's all about demonstrating your skills in action!
✨Be Ready to Dive Deep into Technical Questions
Expect to encounter some technical grilling during the interview. Prepare to discuss statistical methods, algorithms, or maybe even tackle a live coding challenge. We should brush up on tools like Python, R, or SQL—those are key players in the data science field. Don't just know them; be ready to explain your thought process!
✨Help Them Understand Your Work Style
Freelance gigs often mean you'll be working independently, so we need to convey our self-motivation and time management skills. Be prepared to talk about how you’ve handled multiple projects or met tight deadlines before. Sharing your approach to client communication can also give them confidence in your ability to deliver remotely.
✨Pitch Your Value Proposition
When freelancing, it’s crucial to clearly articulate what makes you unique. We should highlight not just technical skills but also the business impact of our projects. Think of a couple of stories where your data insights drove decision-making—this can be a game changer in showing why they should choose you for their freelance needs!
