Data Scientist (ML)

Black Tree Gaming Limited

Job Overview

Location

Remote

Salary

GBP 55,000 - 65,000 yearly

Employment Type

Full-time

Work Arrangement

Remote

Sector

Information Technology & Software

Experience Level

Mid-level (3-5 years)

Application Deadline

May 3, 2026

About the Company

Established in 2001, Black Tree Gaming Limited, operating as Nexus Mods, is the premier platform for video game modding, deeply integrated into the PC gaming community. With over 71 million registered members, 800,000+ mods for 4,000+ games, and 21 billion mod downloads, Nexus Mods is a household name. The company is currently focused on modernizing its product, driving growth, and building robust infrastructure to support the next decade of community-driven modding. Nexus Mods is committed to empowering its users and fostering a vibrant ecosystem. They are investing in their platform to ensure continued innovation and community engagement.

Job Description

We are seeking a highly skilled Data Scientist with a specialization in Machine Learning to join our innovative team at Black Tree Gaming Limited. This is a unique opportunity to build the intelligence layer of our data platform and unlock significant ML capabilities.

You will work with a rich dataset to transform raw information into actionable insights, enhancing user discovery and personalization. Your contributions will directly impact user growth and engagement within our thriving community and ecosystem.

Key responsibilities include developing end-to-end pipelines for mod classification, building recommendation models, and improving search relevance. You will leverage behavioral signals and complex datasets to drive smarter personalization and directly influence key engagement metrics.

To apply for this role, click the Apply button on this page and follow the instructions.

Required Skills

PythonMachine LearningNLPText ClassificationRecommendation SystemsEmbeddingsSimilarity Searchscikit-learnPyTorchClickHousedbt

Key Responsibilities

  • Own the end-to-end pipeline for classification at scale, from data labeling to production models.
  • Transform raw data into structured, high-quality metadata to enhance search, filtering, and personalization.
  • Continuously improve model performance and data quality.
  • Build recommendation models and enhance search relevance to help users find mods faster.
  • Leverage behavioral signals and unique datasets to power smarter personalization.
  • Directly impact engagement by increasing downloads, retention, and overall activity.

Qualifications

  • Experience as a Data Scientist or ML Engineer with a track record of shipping models to production.
  • Strong proficiency in Python and the core ML ecosystem (scikit-learn, PyTorch or similar).
  • Hands-on experience with NLP and text classification.
  • Experience building recommendation systems or search relevance models.
  • Solid understanding of embeddings, similarity search, and operating them at scale.
  • Ability to scope and execute independently with strategic direction.
  • Thrives in fast-moving environments with high autonomy.
  • Pragmatic mindset focused on impact over model accuracy.
  • Familiarity with ClickHouse (warehouse), dbt (transformation), Python, Mixpanel, and Braze.

Benefits & Perks

  • 4-day work week (32 hours) with no reduction in pay.
  • £25 monthly allowance for video games.
  • Employee Assistance Programme.
  • Private BUPA healthcare for you and your family.
  • Flexible training budget.
  • Regular social events.

How to Apply

To apply for this role, click the Apply button on this page and follow the instructions.

The gaming industry is experiencing rapid expansion, driven by advancements in AI and data analytics. This role is pivotal in leveraging these trends to enhance user experience and drive business growth. Key technical skills include Natural Language Processing (NLP), recommendation systems, embeddings, and similarity search. The impact of this position is significant, directly influencing user acquisition, engagement, and retention through intelligent personalization and discovery features. Success will be measured by tangible improvements in user metrics and the successful deployment of scalable ML solutions.

Posted Date

April 17, 2026