Data Science - Statistics

Job Title: Junior Data Science Engineer

About the Client:Our client is an innovative FinTech startup specializing in financial market insights through KPI tracking for publicly listed companies. They leverage proprietary models to estimate quarterly advertising revenues for major tech firms, selling valuable insights to a select group of high-value hedge fund clients. Currently in their third year, the client has achieved £2M ARR and is entering the final stages of an exciting funding round, positioning them strongly for future growth.

Team & Role:You will join a close-knit, collaborative team of 12 (9 Data Scientists, 3 Engineers), reporting directly to the Head of Technology. Your role will focus on building and maintaining KPI trackers and contributing to fundamental regression models and simple time series forecasting tasks.

Role Details:

• Type: Full-time, fully remote

• Salary: £200per day Contract -> £45,000 + Equity

• Contract: Initial 6-month contract, transitioning to permanent

Key Responsibilities:

• Assist in developing and maintaining KPI trackers for publicly listed companies.

• Implement and refine statistical models, particularly regression and time series analysis.

• Perform data queries using SQL and collaborate closely with the wider data science team.

• Ensure high-quality, maintainable code and contribute collaboratively using GitHub.

• Undertake occasional web scraping tasks to support data collection

Ideal Candidate Profile:

• Approximately 1 year of commercial experience in Data Science.

• Strong foundation in statistics, with particular emphasis on regression modeling and basic econometrics.

• Excellent communication skills to clearly explain statistical concepts.

• Proven software development experience (Python required, SQL essential).

• Collaborative coding practices using GitHub.

• Experience with Docker highly desirable.

• Any web scraping experience is a plus.

• Familiarity with time series data is advantageous.

• Interest or experience in integrating LLM technologies or API interactions beneficial.

• Strong interest in finance or economic modeling.

• Academic background in Economics, Statistics, or Mathematics (Masters preferred)

Interview Process:

• Technical assessment (coding samples/projects on GitHub and a Jupyter Lab task).

• Interviews exploring statistical understanding, practical coding ability, problem-solving approach, and overall curiosity.

If you're passionate about statistical modeling, excited by financial markets, and looking to develop your career within a fast-paced, innovative startup, please send your CV