Quantitative Researcher (ML)

NLP PEOPLE; Greater London; On-site; GBP 90,000 - 140,000; Full time

Benefits offered by this job

Competitive salary

Vitality health insurance and dental

38 days of holiday (incl. bank)

Pension scheme

Annual health checks

Learning & development budget £5000

Free gym membership

Cycle to Work scheme

Office breakfast twice a week

Fully stocked fridge and pantry

Social events and games room

Job summary

Dare in City of London is seeking a Quantitative Researcher to join the algorithmic space, building ML capabilities for our liquidity trading teams and delivering models that give traders a competitive edge.

The role requires strong ML, maths and statistics, plus robust Python coding, with experience in production data processing and time-series data management. Collaboration with senior leaders is essential.

Qualifications

• 3+ years experience in machine learning, software engineering and data mining models, with large language modelling (LLM) experience advantageous.
• Background in maths, statistics and algorithms, with ability to write robust scalable Python code.
• Strong understanding of the mathematical and statistical fundamentals underlying ML methods.
• Experience with production data processing: data manipulation, cleansing, aggregation, preprocessing.
• Experience with time-series data, including storage and management.
• Solid experience with ML frameworks (TensorFlow, PyTorch, scikit-learn, HuggingFace).
• Ability to work with analytical teams to build dashboards that prove ML value in production.

Responsibilities

• Using Dare’s proprietary trading data and models to drive trading PNL.
• Developing trading indicators and ML-powered strategies.
• Partnering with quantitative research and algorithmic trading technology teams.
• Collaborating with the CEO and senior stakeholders to shape a strategy delivering competitive ML models.

Skills

ML algorithms

Python

Time-series data

Statistical methods

Production data processing

Data manipulation

Dashboard development

LLMs

Tools

TensorFlow

PyTorch

scikit-learn

HuggingFace

Job description

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.

Company:

Dare

Qualifications:

Language requirements:

Specific requirements:

Educational level:

Level of experience (years):

Senior (5+ years of experience)

Tagged as: Data Mining, Industry, Language Modeling, Machine Learning, NLP, United Kingdom