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Data Scientist

Role overview

Qualifications

  • Proficiency in Python
  • Strong Statistical knowledge
  • Some experience working with databases and using SQL
  • Strong Excel skills

Responsibilities

  • Write robust, commented scripts to collect, clean, process, and save data
  • Analyze data, build, validate, and test prototype models in Jupyter
  • Construct automated pipelines for moving and processing data between different sources
  • Produce data visualisations and dashboards in Python and/or PowerBI

Key facts

Hard skills

Other skills

  • Microsoft Excel
  • Self-Motivation

About the company

Oxford Data Plan logo

Oxford Data Plan

  • Data & Analytics
  • SME
  • 51–200
Oxford Data Plan delivers institutional-grade alternative data and daily KPI estimates for 250+ global equities, enabling hedge funds and asset managers to identify inflections ahead of consensus. We combine proprietary and exclusive datasets—including a global receipt panel, exclusive advertising agency partnerships, —with multi-signal modeling to produce point-in-time estimates across 500+ KPIs. Our coverage spans TMT, consumer, financials, and real economy sectors, with daily delivery designed for systematic and fundamental workflows. Core capabilities include: • Daily revenue, orders, and operational metrics with 12-hour delivery lag • Advertiser-level digital spend tracking across 15,000+ brands and major platforms • Sector insights covering digital advertising, food delivery, airlines, and classifieds • Historical backtesting and out-of-sample validation for every tracker Built by former buy-side analysts, our platform is optimized for alpha generation, not data exploration. Clients receive structured feeds with full point-in-time integrity. Oxford Data Plan is trusted by leading quantitative and fundamental investors seeking differentiated signal with institutional rigor.

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Job description

We are looking for a full-time data scientist to work with us on the following areas:

  1. Product deployment – creating, deploying, and maintaining new KPI trackers.

  2. Research – finding, collecting, and evaluating new data sources, developing new experimental product features for end-users, improving our methodology.

Reporting to the Data Science Manager you will:

  • Write robust, commented scripts to collect, clean, process, and save data.

  • Analyze data, build, validate, and test prototype models in Jupyter.

  • Construct automated pipelines for moving and processing data between different sources.

  • Produce data visualisations and dashboards in Python and/or PowerBI.

  • Deploying new jobs using Docker and AWS technologies.

  • Monitoring, debugging and maintaining production code.

To be successful in the role you should have:

  • Proficiency in Python:

    • Ability to write functional, reproducible, and well documented code.

    • Proficient with typical data scientist modules (pandas, numpy, matplotlib, scikit-learn).

    Strong Statistical knowledge:

    • Good understanding of fundamental statistical concepts (e.g. bias, variance, R-squared).

    • Good understanding of the theory and practice of linear regression.

    Self-motivated and autonomous individual.

    • Significant training and support will be provided; however, we expect a successful candidate to quickly take full ownership of their work and proactively make an impact in ODP.

    Some experience working with databases and using SQL.
    Strong Excel skills.
    Experience with Git.
    Interest in finance.

Desirable skills
Proficient in web-scraping – at least with requests, ideally with selenium or other web-scraping packages.
Software development – experience in managing installable python packages is very valuable.
Proficient SQL and database knowledge and experience.
Advanced knowledge of time-series modelling or Bayesian statistics.
Experience working with AWS.
Experience creating visualisations with Power BI.
Proficiency with Git.
Experience/proficiency with Docker.
Good experience/knowledge of the finance sector.

Applicants should be fluent in English and have an interest in Finance and Data Science.

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