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Cerberus Capital Management · 13 hours ago

Data Scientist

NYC Metro Area

Full-time

Onsite

Entry, Mid Level

$160K/yr - $200K/yr

Cerberus Capital Management is a growing team of AI specialists working to transform how an alternative investment firm leverages technology and data. The Data Scientist will work on high-impact projects, developing machine learning solutions that provide actionable insights and support decision-making across investment desks and portfolio companies.

FinanceFinancial ServicesImpact Investing

No H1B

Responsibilities

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

Qualification

Machine LearningStatistical AnalysisPythonSQLDeep LearningModel DeploymentCollaborationCommunicationProblem-Solving

Required

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

Skilled in building data pipelines and ML models using modern libraries across multiple domains

Proficient in SQL, with the ability to write efficient, maintainable queries and manage data pipelines for analytics and modelling workflows

Familiarity with deploying models into production environments, collaborating with engineering teams, and using tools like MLflow or Weights & Biases for experiment tracking and reproducibility

Ability to translate complex problems into tractable modelling approaches

Strong problem-solving skills, intellectual curiosity, and a pragmatic approach to delivering solutions that drive measurable business value

Demonstrated experience working in collaborative development environments using tools like Git and Azure DevOps

Proven ability to work cross-functionally with data scientists, engineers, and non-technical stakeholders to translate business needs into technical solutions and ensure successful delivery and adoption