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- Tasks: Join a dynamic team to develop ML capabilities for trading strategies.
- Company: Leading energy trading company with a focus on innovation and collaboration.
- Benefits: Competitive salary, health insurance, 38 days holiday, and personal development budget.
- Other info: Great workplace culture with social events, games room, and opportunities for career growth.
- Why this job: Make a real impact in a fast-paced environment while working with cutting-edge technology.
- Qualifications: 3+ years in machine learning, strong Python skills, and a solid maths background.
The predicted salary is between 60000 - 80000 £ 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’.
Quantitative Researcher (ML) employer: Dare
Contact Detail:
Dare Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher (ML)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Dare. A friendly chat can open doors that applications alone can't.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a project that highlights your machine learning expertise. Bring it up during interviews to demonstrate your hands-on experience.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions for quantitative researchers. Mock interviews with friends can help you nail your responses.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you're genuinely interested in being part of the Dare team.
We think you need these skills to ace Quantitative Researcher (ML)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Quantitative Researcher role. Highlight your experience with machine learning algorithms and Python coding, as these are key for us. Use specific examples that showcase your skills and achievements in relevant projects.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you're passionate about the role and how your background aligns with our needs. Be sure to mention any experience you have with data-intensive markets or algorithmic trading, as this will resonate with us.
Showcase Your Technical Skills: We want to see your technical prowess! Include details about your experience with machine learning frameworks like TensorFlow or PyTorch. If you've worked with time-series data or cloud-based solutions, make sure to highlight that too!
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our culture and values before you apply.
How to prepare for a job interview at Dare
✨Know Your Algorithms
Make sure you brush up on your machine learning algorithms and their mathematical foundations. Be prepared to discuss how you've applied these in real-world scenarios, especially with large language models. This will show that you understand the concepts deeply, not just the code.
✨Showcase Your Coding Skills
Since robust Python coding is crucial for this role, practice writing clean, scalable code. You might be asked to solve a problem on the spot, so being comfortable with coding challenges can really set you apart from other candidates.
✨Understand the Business Context
Familiarise yourself with the energy trading sector and how machine learning can drive trading PNL. Being able to connect your technical skills to the business's goals will demonstrate your strategic thinking and ability to collaborate with senior leaders.
✨Prepare for Collaboration Questions
Expect questions about teamwork and collaboration, especially since you'll be working closely with various teams. Think of examples where you've successfully partnered with others to deliver projects, particularly in high-pressure environments or with tight deadlines.