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For Companies At a Glance
- 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.
- Why this job: Make a real impact in a fast-paced environment using cutting-edge technology.
- Qualifications: 3+ years in machine learning, strong Python skills, and a solid maths background.
- Other info: Great workplace culture with social events, games room, and opportunities for growth.
The predicted salary is between 36000 - 60000 £ per year.
Overview
City of London
Permanent, Full-time – Onsite
Who we are:
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.
What you’ll be doing
The Quantitative Researcheris a key role within the algorithmic technical space at Dare. Working closely with a talented algorithmic andtechnical team to build a platform that delivers ML capabilities to ourLiquidity 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, withlarge 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. We want someone who understands the methods rather than just calling functions from existing ML packages.
- Experience with production data processing. That includes 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 (TenserFlow, 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 fulfill 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’. Read more about our culture and what our team says about us here.
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Quantitative Researcher (ML) employer: Dare
Contact Detail:
Dare Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher (ML)
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, conferences, or even online webinars. Building relationships can open doors to opportunities that aren’t even advertised.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your machine learning projects or any relevant work. This gives potential employers a taste of what you can bring to the table.
✨Ace the Interview
Prepare for technical interviews by brushing up on your algorithms and coding skills. Practice common ML problems and be ready to discuss your thought process. Remember, it’s not just about getting the right answer but how you approach the problem!
✨Apply Through Our Website
We encourage you to apply directly through our website. It shows your genuine interest in joining us at Dare and helps us keep track of your application more efficiently. Plus, who doesn’t love a smooth application process?
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 shows us you’re keen on joining our team at Dare!
How to prepare for a job interview at Dare
✨Know Your ML 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 in trading contexts. This will show that you understand the methods deeply, not just the surface-level functions.
✨Showcase Your Coding Skills
Since robust Python coding is crucial for this role, be ready to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice writing clean, efficient code beforehand. Familiarise yourself with libraries like TensorFlow and PyTorch, as they may come up in conversation.
✨Understand the Business Context
Dare is all about combining trading expertise with data science. Research the company’s approach to energy trading and think about how your skills can contribute to their goals. Being able to articulate how your work can provide a competitive edge will impress the interviewers.
✨Prepare for Collaboration Questions
This role involves working closely with various teams, including senior leaders. Prepare examples of past collaborations where you successfully built relationships and delivered results. Highlight your communication skills and ability to work in a team, as these are key to thriving at Dare.
