At a Glance
- Tasks: Join a dynamic team to develop ML strategies that enhance trading performance.
- Company: Dare, an innovative energy trading company in the heart of London.
- Benefits: Enjoy 38 days holiday, health insurance, gym membership, and a personal development budget.
- Other info: Collaborative culture with opportunities for growth and a focus on diversity.
- Why this job: Make a real impact in a fast-paced environment with cutting-edge technology.
- Qualifications: 3+ years in machine learning, strong Python skills, and a solid maths background.
The predicted salary is between 63000 - 77000 £ per year.
We are an energy trading company generating liquidity across global commodities markets. We combine deep trading expertise with proprietary technology and the power of data science to be the best-in-class. Our understanding of volatile, data-intensive markets is a key part of our edge.
At Dare, you will be joining a team of ambitious individuals who challenge themselves and each other. We have a culture of empowering exceptional people to become the best version of themselves.
The Quantitative Researcher is a key role within the algorithmic technical space at Dare. Working closely with a talented algorithmic and technical team to build a platform that delivers ML capabilities to our Liquidity trading teams. These teams are responsible for delivering products for internal customers. Setting and delivering a consistent, scalable approach to machine learning across the organisation is one of the key success criteria for this role. The role requires building relationships and collaborating with Senior Leaders across the business to shape a strategy that delivers models that provide our traders with a competitive edge.
Using Dare’s proprietary trading data and models to drive trading PNL. Developing trading indicators and strategies powered by machine learning. Partnering with quantitative research and algorithmic trading technology teams. Collaborating with the CEO and other senior stakeholders to combine domain knowledge with engineering expertise.
What you’ll bring:
- 3+ years experience in machine learning algorithms, software engineering, and data mining models, with large language modelling (LLM) experience being advantageous.
- A background in maths, statistics, and algorithms, with the capability to write robust scalable Python code.
- A strong understanding of the mathematical and statistical fundamentals on which the ML methods are based.
- Experience with production data processing, including data manipulation, data cleansing, aggregation, efficient (pre-)processing, etc.
- Experience with time-series data, including storage and management.
- A strong understanding through the usage of machine learning frameworks (TensorFlow, PyTorch, sci-kit-learn, Huggingface).
- Ability to work with analytical teams to build dashboards that prove the value of the machine learning capabilities as we deliver models to our production environments.
Desirable:
- Experience working with real-time data systems.
- Experience working with cloud-based solutions.
Benefits & perks:
- Competitive salary
- Vitality health insurance and dental cover
- 38 days of holiday (including bank holidays)
- Pension scheme
- Annual Bluecrest health checks
- A personal learning & development budget of £5000
- Free gym membership
- Specsavers vouchers
- Enhanced family leave
- Cycle to Work scheme
- Credited Deliveroo dinner account
- Office massage therapy
- Freshly served office breakfast twice a week
- Fully stocked fridge and pantry
- Social events and a games room
Diversity matters: We believe in a workplace where our people can fulfil their potential, whatever their background or whomever they are. We celebrate the breadth of experience and see this as critical to problem-solving and to Dare thriving as a business. Our culture rewards curiosity and drive, so the best ideas triumph and everyone here can make an impact.
Please let us know ahead of the interview and testing processes if you require any reasonable adjustments or assistance during the application process. We're also proud to be certified a 'Great Place to Work'.
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