National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Data Scientist, AI/ML, Associate

Cerberus Capital Management
London
2 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist -UAE National, AWS Generative AI Innovation Center

Data Scientist -UAE National, AWS Generative AI Innovation Center

Data Scientist / R - Manchester Based

Junior Data Scientist

Data Scientist II, Regulatory, Intelligence, Safety and Compliance (RISC)

Data Scientist II, Regulatory, Intelligence, Safety and Compliance (RISC)...

Data Scientist at Cerberus Capital Management


As aData Scientistin our AI team, you will contribute to the firm’s objectives by delivering rapid and scalable solutions that unlock value for Cerberus desks, portfolio companies, or other businesses/investments. You’ll do this by designing, implementing, and deploying machine learning systems that help our desks and portfolio companies make better business decisions and ultimately drive value. You may also participate in due diligence or pricing analyses of future investments, etc.


Responsibilities:


Build and deliver AI systems as an individual contributor and in teams.

  • Delivery focused:Help design solutions using a rigorous hypothesis-based approach, partner with cross-functional technical teams, and execute the development with a focus on impact.
  • Agile and pragmatic: Rapidly and iteratively deliver results in high-pressured projects, with skill and creativity to pivot quickly as needed to create the most value.
  • Contemporary and innovative approach:Develop novel solutions using modern platforms, languages, and tools; build IP into re-usable software packages.
  • Structured approach:Bring order to disparate requirements with high tolerance for ambiguity, very strong problem-solving ability, and excellent stakeholder engagement skills.


Communicate results in a compelling way to senior business executives.

  • Communicator:Break down complex concepts and problems into succinct components for a range of clients and colleagues at all levels of seniority.
  • Storytelling:Be a storyteller capable of delivering insights in a compelling manner.


Build a reputation as a trusted technologist and member of the team.

  • Technology polymath:experience with a wide range of technology and can learn and develop any solutions across the full data science lifecycle and application stack.
  • Test & learn mentality:Challenge our current best thinking, test ideas, and iterate rapidly.
  • Creativity:Invent new analyses and methods to solve key business problems.
  • Trusted voice:Establish reputation of delivering on commitments; build high-trust relationships.
  • Expertise:Develop deep subject matter expertise in valuable areas for the business.


Requirements:

  • 4+ years of experience
  • A degree in STEM field or equivalent and advanced degree.
  • Strong knowledge of statistics, machine learning, forecasting, NLP, computer vision, optimisation.
  • Python programmer with experience building data pipelines and statistical / machine learning models. Additional languages preferred, particularly HTML+CSS+JavaScript, or low-level compiled languages such as C/C++.
  • Proficiency in SQL. Ability to write efficient and robust queries.
  • Experience with DevOps process for model deployment and unit testing.
  • Proof of work in cloud environments, especially MS Azure, is a plus.
  • Proof of work in collaborative development environment (Git, Azure DevOps, JIRA).
  • Strong intellectual curiosity, mathematical problem solving, and effectiveness in a team.


About Us:

Established in 1992, Cerberus Capital Management, L.P., together with its affiliates, is one of the world's leading private investment firms. Through its team of investment and operations professionals, Cerberus specializes in providing both financial resources and operational expertise to help transform undervalued and underperforming companies into industry leaders for long-term success and value creation. Cerberus holds controlling or significant minority interests in companies around the world.


The Firm’s proprietary operations team,Cerberus Operations and Advisory Company, LLC (COAC), employs world-class operating executives to support Cerberus’ investment teams in the following areas: sourcing opportunities, conducting highly informed due diligence, taking interim management roles, monitoring the performance of investments and assisting in the planning and implementation of operational improvement initiatives at Cerberus’ portfolio companies.


Cerberus Technology Solutions is an operating company and subsidiary of Cerberus Capital Management focused exclusively on leveraging emerging technology, data, and advanced analytics to drive transformations. Our expert technologists work closely with Cerberus investment and operating professionals across our global businesses and platforms on a variety of operating initiatives targeted at improving systems and generating value from data.

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Jobs UK 2025: 50 Companies Hiring Now

Bookmark this guide—refreshed every quarter—so you always know who’s really expanding their data‑science teams. Budgets for predictive analytics, GenAI pilots & real‑time decision engines keep climbing in 2025. The UK’s National AI Strategy, tax relief for R&D & a sharp rise in cloud adoption mean employers need applied scientists, ML engineers, experiment designers, causal‑inference specialists & analytics leaders—right now. Below you’ll find 50 organisations that have advertised UK‑based data‑science vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the kind of employer—& culture—that suits you. For every company you’ll see: Main UK hub Example live or recent vacancy Why it’s worth a look (tech stack, mission, culture) Search any employer on DataScience‑Jobs.co.uk to view current ads, or set up a free alert so fresh openings land straight in your inbox.

Return-to-Work Pathways: Relaunch Your Data Science Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like stepping into a whole new world—especially in a dynamic field like data science. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s data science sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve gained and provide mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for data science talent in the UK Leverage your organisational, communication and analytical skills in data science roles Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to data science Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to data science Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as a data analyst, machine learning engineer, data visualisation specialist or data science manager, this article will map out the steps and resources you need to reignite your data science career.

LinkedIn Profile Checklist for Data Science Jobs: 10 Tweaks to Elevate Recruiter Engagement

Data science recruiters often sift through dozens of profiles to find candidates skilled in Python, machine learning, statistical modelling and data visualisation—sometimes before roles even open. A generic LinkedIn profile won’t suffice in this data-driven era. This step-by-step LinkedIn for data science jobs checklist outlines ten targeted tweaks to elevate recruiter engagement. Whether you’re an aspiring junior data scientist, a specialist in MLOps, or a seasoned analytics leader, these optimisations will sharpen your profile’s search relevance and demonstrate your analytical impact.