Data Scientist

Legend Corp; City of London; On-site; GBP 50,000 - 70,000; Full time

Job summary

A leading technology company in London is seeking a Data Scientist to drive predictive modeling and analytical solutions. This role will involve collaborating with cross-functional teams to build impactful data models and ensure data-driven decisions throughout the organization. Candidates should possess a Master’s degree in a quantitative field as well as proficiency in SQL and Python. The position offers a supportive environment with numerous opportunities for professional growth and mentorship.

Benefits

Annual discretionary bonus

Paid annual leave

Long term incentive plan

Events for team building

Work-life flexibility

Qualifications

• Master’s degree in Math, Physics, Engineering, Computer Science, or Economics.
• Experience with data science techniques applied to business problems.
• Demonstrated self-motivation and strong research mindset.

Responsibilities

• Scope and validate analytical solutions aligned with business objectives.
• Prepare and clean data for accuracy and usability.
• Build models using various data science techniques under mentorship.
• Monitor and document model performance, refining as necessary.
• Present findings to diverse audiences for decision-making.

Skills

SQL

Python

Statistical analysis

Collaboration in cross-functional teams

Self-direction

Education

Master’s degree in a quantitative field

Tools

Git

Github

Bash

Job description

We’re Legend. The team quietly building #1 products that make noise in the most competitive comparison markets in the world. iGaming. Sports Betting. Personal Finance.

We exist to build better experiences. From amplified career paths to supercharged online journeys — for our people and our users, we deliver magic rooted in method. With over 550 Legends and counting, we’re helping companies turbocharge their brand growth in over 22 countries worldwide.

If you’re looking for a company with momentum and the opportunity to progress at pace, Legend has it.

Unlock the Legend in you.

The Role

Legend is hiring a Data Scientist to join our central Data & Analytics function, working alongside data analysts, engineers, and senior data scientists. The role contributes to the development of predictive models and analytical products that drive decision‑making across marketing, product, and commercial teams.

This position is ideal for someone ready to apply numerical modelling and engineering skills to real‑world business problems, working within a supportive, high‑performing environment where ownership, rigour, and learning are prioritised.

Projects span various data science domains, including anomaly detection, forecasting, optimisation, recommendations, ranking, experimentation, and AI, each focused on measurable business outcomes and delivered through collaboration with data and product teams.

In this role, we value diverse perspectives and encourage you to apply even if you don't meet every qualification listed.

Your Impact

• Scope and validate analytical solutions aligned with clear business objectives
• Prepare and clean data in collaboration with engineers and analysts to ensure accuracy and usability
• Build models (under mentorship) using the full range of data science techniques, from statistics and econometrics to machine learning and mathematical optimisation.
• Contribute to model development across supervised and unsupervised ML techniques under mentorship
• Monitor and document model performance, flagging issues and iterating where appropriate
• Present findings clearly to technical and non‑technical audiences to inform decision‑making across teams

What You’ll Bring

• Master’s degree in a quantitative field (e.g. Mathematics, Physics, Engineering, Computer Science, Economics)
• Self‑motivated with a researcher’s mindset to tackle ambiguous challenges and drive solutions with minimal guidance
• Demonstrated experience applying data science techniques to business problems
• Proficient in SQL, Python, and standard data science libraries
• Foundational engineering skills, including version control (Git), collaborative development tools (Github) and command‑line tools (Bash)
• Self‑directed learner who thrives in cross‑functional teams

Nice to haves

• A PhD or demonstrated research experience
• Exposure to cloud‑based data environments (Snowflake, AWS, Airflow or similar)
• Experience working on model deployment and Docker containers
• Knowledge of A/B testing frameworks

The Interview Process

• 1st: Initial Chat with Talent Partner (30 mins via Zoom)
• 2nd: Interview with the hiring manager (1 hour video via Zoom)
• 3rd: Technical Task with the hiring team (1 hour video via Zoom)
• 4th: Final interview with our team (1 hour video via Zoom)

Why Legend?

• Super smart colleagues to work alongside and learn from.
• Tailored flexibility for your work‑life balance.
• Annual discretionary bonus to reward your efforts.
• Paid annual leave PLUS a well‑deserved break to recharge your batteries during the festive season! Our offices are closed between Christmas and New Year’s, allowing you to enjoy downtime without dipping into your annual allowance.
• Long term incentive plan so we can all share in the growth and success of Legend.
• Exciting global Legend events, where we unite in person to ignite our shared passion and unveil the exciting strategies for the year ahead!
• Unlock your full potential by joining the Legend team. To support you on this journey, we provide an extensive array of benefits and perks, as outlined in our global offerings above. For country specific benefits please reach out to your talent partner.

Legend is an Equal Opportunity Employer, but that’s just the start. We believe different perspectives help us grow and achieve more. That’s why we’re dedicated to hiring and developing the most talented and diverse team‑ which includes individuals with different backgrounds, abilities, identities and experiences. If you require any reasonable adjustments throughout your application process, please speak to your Talent Partner or contact the team at [e-mail], and we’ll do all we can to support you.