Data Scientist

Location: London, UK (London Bridge)

Work pattern: Full-time (Hybrid), permanent, PAYE

Salary: Mid-level: £40,000 - £65,000 per annum, DOE, plus staff EMI Options scheme

Reporting line: to Senior Data Scientist

Division: Data and Technology

We are looking for a Data Scientist with 2+ years of experience to join our fast-growing Data and Technology team and play a crucial role in developing and enhancing our NLP models and model framework. As a company, we harmonise anonymised consumer transaction data and create products for investment and corporate clients. Our products give real-time insight on revenue shifts, market share, consumer switching and online/store sales.

About you

You are passionate about building scalable, secure and efficient data science products. You will have had real-world experience training machine learning models, either as a professional data scientist or in a closely adjacent role.

You feel comfortable working in a fast-paced, rapidly changing start-up environment, which will require resilience and the ability to deal with ambiguity and less developed processes/systems.

Key responsibilities

1. Analyse and develop NLP models for text classification to homogenise and tag transaction data
2. Assist in developing cloud infrastructure and data pipelines for deploying models (MLOps)
3. Conduct exploratory data analysis for commercial, auditing and compliance teams
4. Develop and implement efficient strategies for creating high-quality labelled training datasets, leveraging automation, weak supervision, active learning techniques and AI

Essential skills

1. Excellent knowledge of Python for data science
2. Strong SQL skills
3. Experience building, deploying and monitoring machine learning models on Azure, AWS and/or Databricks or similar platforms
4. Experience with developing production code along with an understanding of source control via Git
5. Fast learner and comfortable with uncertainty and change
6. Good problem solving, communication and collaboration skills

Desirable skills

1. Experience working in NLP - Unsupervised Text Classification of unstructured data and/or working with LLMs
2. Experience in the application of Software Engineering Principles in Data Science
3. Experience in Big Data technologies such Spark/PySpark
4. Experience working in Financial Services

About Fable Data

Fable Data is a pioneering data and technology company transforming financial data into actionable insights. Our mission is to deliver cutting-edge solutions that empower businesses to make informed decisions. We are a small, collaborative and tight-knit team. Our values encapsulate this: "We do the right thing", "We work and grow, together" and "We solve difficult things in smart ways".

Benefits:

1. 30 days holiday plus bank holidays
2. Staff EMI options scheme (eligible after 6 months)
3. Medical insurance
4. A flexible, hybrid working environment with the option to work from home 3-4 days a week
5. Opportunity to work in a dynamic and innovative company.
6. Professional development and career growth opportunities.

The Interview Process

1. Pre-screening call - online (30 mins.), to assess initial interest and suitability
2. Competency-based Interview - two or more stages, online/in the office (1 hour) with competency-based and behavioural questions to assess technical skills, practical knowledge and overall role fit

Decision

1. Offer of Employment issued
2. "Get to know us" meetings and/or calls with other members of Fable Data team for you to learn more about the role, company and future colleagues while considering the offer

Please note that applicants must have the right to work in the UK

Fable Data is an equal opportunity employer and does not discriminate on the grounds of a person's gender, marital status, race, religion, colour, age, disability, or sexual orientation. All candidates will be assessed based on merit, qualifications, and their ability to perform the role requirements.

How to Apply: Interested candidates should apply directly via the Apply For This Job link or relevant jobs boards/LinkedIn.