Data Scientist

Data Scientist [Analyst / Associate]

About the job

As a Data Scientist on the AI team at Cerberus, you’ll work on high-impact projects that combine the pace of a startup with the reach of a global investment platform. Our team partners directly with internal investment desks as well as portfolio companies across industries to deliver machine learning solutions that unlock value and accelerate decision-making.

Your work will range from developing and validating robust predictive models for pricing and valuation across diverse asset classes to dynamically optimizing prices under changing market conditions. You’ll be expected to translate complex data into actionable insights and ensure your solutions are not only technically sound but also adopted and delivering measurable business value, supporting deal team members and portfolio company executives.

We’re looking for data scientists who are passionate about impact—those who bring deep statistical knowledge, thrive in fast‑paced environments, and want to see their models deployed, used, and making a difference.

• Build and deliver AI solutions:
  Design and implement advanced models and systems as both an individual contributor and as part of cross‑functional teams.
• Drive impact through execution:
  Apply a hypothesis‑driven approach to design solutions, collaborate with technical teams, and deliver results that create measurable business value.
• Work in an agile, fast‑paced environment:
  Rapidly iterate and adapt to changing priorities, using creativity and pragmatism to maximize outcomes.
• Leverage modern tools and methods:
  Develop innovative solutions using contemporary platforms, languages, and frameworks, and package IP into reusable components.
• Communicate insights effectively:
  Translate complex technical concepts into clear, compelling narratives that drive understanding and action across technical and non‑technical audiences.
• Build trust through delivery:
  Establish credibility by delivering high‑quality solutions, challenging assumptions constructively, and iterating quickly in response to feedback.
• Develop broad technical capability:
  Work across the full data science lifecycle, continuously learning and applying new technologies.

• Real estate portfolio valuation:
  Work on developing advanced valuation models for real estate portfolios using internal and external data sources. This includes building predictive models with uncertainty estimates, improving model performance through rigorous evaluation, and creating data pipelines to support modelling and analytics. You’ll also prototype processes downstream of valuation models, such as optimization approaches, to enhance pricing strategies, collaborating with stakeholders to integrate these solutions into business processes.
• Price optimization & forecasting for goods:
  Develop machine learning models to forecast demand and optimize pricing strategies for goods sold by a portfolio company. You’ll build predictive models that incorporate seasonality and competitive pricing data, while quantifying uncertainty and maintaining model explainability to support robust, transparent decision‑making.

We’re a small, high‑impact team with a broad remit and diverse technical backgrounds. We don’t expect any single candidate to check every box below — if your experience overlaps strongly with what we do and you’re excited to apply your skills in a fast‑moving, real‑world environment, we’d love to hear from you.

• Strong technical foundation:
  Degree in a STEM field (or equivalent experience) with hands‑on expertise in at least two of applied statistics, machine learning, forecasting, NLP, or optimization. Experience with uncertainty quantification, model evaluation, and statistical inference is highly valued.
• Python expertise:
  • Data science stack:
    Num Py, pandas / polars, scikit‑learn, XGBoost, LightGBM
  • Deep learning:
    PyTorch, JAX
  • Statistical programming:
    Num Pyro, PyMC
  • Data skills:
    Proficient in SQL, with the ability to write efficient, maintainable queries and manage data pipelines for analytics and modelling workflows.
• Model development & deployment:
  Familiarity with…