Senior Data Scientist

Roark Capital

Atlanta (GA)

On-site

USD 150,000 - 210,000

Full time

11 days ago

Get more replies from employers

Send a job-specific resume in minutes.

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Life insurance

Long-term disability insurance

401k with employer match

Paid time off

Office snacks

Job summary

Roark Capital is seeking a Senior Data Scientist in Atlanta to ship production-grade ML models across multiple brands and use-cases. You will own end-to-end development—from framing problems to deployment and monitoring—while collaborating with investment teams and internal stakeholders.

The role emphasizes strong Python, MLOps, and cloud deployment experience, with opportunities to raise engineering standards and impact Roark’s portfolio performance.

Qualifications

Bachelor's degree in a quantitative discipline; Master’s preferred.
5–8 years of applied data science experience with senior autonomy.
Shipped models across forecasting, regression, and classification.
Owned models in production with deployment, monitoring, and maintenance.
Strong Python, Git, code review and packaging.
Cloud deployment and MLOps fundamentals (CI/CD, reproducibility).
Experience raising engineering standards and delivering to stakeholders.
Authorized to work in the United States; role based in Atlanta, GA.

Responsibilities

Own ML models end-to-end — framing, deployment, monitoring and maintenance.
Translate business problems into modeling approaches with an 80/20 mindset.
Write clean, tested Python; participate in code reviews and packaging.
Deploy and operate models on Google Cloud Platform (Vertex AI, BigQuery, Cloud Run).
Raise engineering standards and mentor teammates.
Partner with investment teams and internal clients to deliver analysis and tools.
Author reusable IP — libraries, templates, and standards for Roark's businesses.
Get up to speed quickly on new projects and brands across Roark's portfolio.
Ensure rigor in model validation, monitoring, and documentation.
Stay current on ML advances relevant to private equity and consumer businesses.

Skills

Python

SQL

Machine learning

MLOps

Cloud platforms

Data analysis

Communication

Stakeholder management

Education

Bachelor's degree

Master's degree preferred

Tools

Vertex AI

BigQuery

Cloud Run

Git

Docker

Job description

Roark is an Atlanta-based private equity firm with over $41 billion in assets under management. Roark focuses on investments in consumer and business service companies, with a specialization in franchise and franchise-like business models. Roark prides itself on being a trusted partner for management and business owners. We believe that successful partnerships begin with providing a compelling value proposition to all business constituencies. A win‑win‑win approach leads to a positive business environment where all stakeholders – customers, employees, franchisees, strategic partners, service providers, management and shareholders – share in the growth and success of our businesses. We want to partner with entrepreneurs and executives who share this vision. Roark brands generate approximately $100 billion in annual system revenues from 117,000+ locations located in 50 states and 120 countries.

Our portfolio companies span multiple industries including food, restaurants, consumer and business services, health, wellness and fitness, and education and youth activities. We are best known for our portfolio companies such as, Dunkin', Jimmy John's, Jamba, Orangetheory, Mathnasium, Drybar just to name a few. Roark is growing our in-house Data and Analytics team, with the goal of better leveraging advanced analytics, data science, and machine learning to make sound investment decisions and guide our owned businesses to profitable growth. We are seeking a Senior Data Scientist to ship production-grade models and tools across Roark investment use-cases and our brands. We are a fast-paced, growing, and entrepreneurial team, and this role will enjoy working across many topics and brands as we build durable competitive advantage in how we underwrite investments and scale portfolio performance.

This is a hands-on, senior individual-contributor role for a generalist data scientist with strong MLOps and software-engineering depth. Typical work spans regression modeling, demand forecasting, customer and unit economics modeling, pricing and promotion analytics, classification problems, and GenAI productivity tooling. You will own models end-to-end — from framing the problem through deployment, monitoring, and maintenance, in addition to taking existing models built by others and transforming them into to be more reusable and/or put into production.

We want a self-sufficient developer who raises the craft of the people around them. The team will look to this individual to help up-level their capabilities. The ideal candidate is comfortable across a wide variety of tasks, gets up to speed on a new project quickly, and adds value in an agile fashion. They work in an 80/20 style and do not need the perfect dataset to get started. This role partners closely with investment teams, our owned businesses, and Data & Software Engineering to deliver scalable, production-ready solutions that drive real business impact. This position is expected to be in-office to support collaboration and culture building.

POSITION RESPONSIBILITIES

Own machine learning models end-to-end — build, deploy, monitor, and maintain them in production, including forecasting, regression, and classification, beyond proof-of-concept
Translate ambiguous business problems into well-defined modeling approaches and data requirements, working in an 80/20 style without waiting for a perfect dataset
Write clean, tested, reusable Python; participate in code review; and apply strong software craft, including Git and packaging
Deploy and operate models on the cloud (Google Cloud Platform preferred — Vertex AI, BigQuery, Cloud Run), applying MLOps fundamentals: CI/CD for ML, reproducibility, deployment, and monitoring
Raise the engineering and modeling standards of those around you — teaching craft and lifting team quality, not only your own output
Partner directly with investment teams, owned-business stakeholders, and internal clients to deliver analysis and tools that drive decisions
Author reusable IP — internal libraries, templates, and standards documentation — that scales across Roark's businesses and target sectors
Get up to speed quickly on new projects and brands, adding value across a wide variety of tasks in an agile fashion
Ensure rigor in model validation, performance monitoring, and documentation, balancing sophistication with interpretability, speed, and impact
Stay current on advances in machine learning, AI, and applied analytics relevant to private equity and consumer businesses

POSITION QUALIFICATIONS

Bachelor's degree in a quantitative discipline (computer science, data science, engineering, mathematics, statistics, economics, or similar), Master\'s Degree preferred.
5–8 years of applied data science experience, operating with senior-level autonomy and requires minimal coaching or guidance
Demonstrated breadth: has shipped a variety of models; from forecasting, regression, and classification work, and is comfortable across the core algorithm families
Has owned at least one model in production — deployed, monitored, and maintained (not proof-of-concept only)
Strong software craft in Python: clean, tested, reusable code; Git; code review; and packaging
Cloud deployment experience (Google Cloud Platform preferred — Vertex AI, BigQuery, Cloud Run) and MLOps fundamentals you can teach others: CI/CD for ML, reproducibility, deployment, and monitoring
Evidence of having raised others\' engineering standards, not only your own
Client- and stakeholder-facing delivery experience, Either Consulting engagements or as cross-functional business support.
Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future; role is based in Atlanta, GA

CORE AREAS OF DESIRED EXPERTISE

Regression and classification across a range of business problems
Pricing and promotion analytics
Marketing Analytics
Customer and unit economics modeling
Experiment design and measurement
Forecasting and demand prediction, including unit-level forecasting

TOOLS AND PLATFORMS

Python and SQL
Cloud platforms, Google Cloud Platform preferred (Vertex AI, BigQuery, Cloud Run)
MLOps tooling: CI/CD for ML, reproducibility, deployment, and monitoring
Generative AI coding productivity tools (Claude Code, Cursor, etc.) – Candidate should be comfortable using AI tools to be a more efficient and stronger Data Scientist.

IDEAL CANDIDATES MAY ALSO POSSESS THE FOLLOWING QUALIFICATIONS

Generative AI / agentic development experience — Mastra, LangGraph, RAG, and LLM applications
Domain adjacency: QSR, multi-unit consumer, retail, CPG, or franchise businesses; unit-level forecasting
Orchestration and pipeline experience: Airflow, dbt, Dataflow
Has authored reusable IP — internal libraries, templates, or standards documentation

DESIRED PERSONAL AND LEADERSHIP CHARACTERISTICS

High standards of integrity, accountability, character, and professionalism
A self-sufficient Developer who delivers on time analysis and code
Raises the craft of those around them rather than only their own output
Hands-on, pragmatic, and results-oriented, with a bias for action and a willingness to roll up sleeves to get the job done
Comfortable working across a wide variety of tasks; gets up to speed on a new project quickly and adds value in an agile fashion
Works in an 80/20 style — does not need the perfect dataset to get started, and balances speed and impact with technical rigor
Thrives in a fast-paced, high-demand environment with multiple competing priorities; self-starter with a sense of urgency to deliver under tight deadlines
Low-ego team player who enjoys collaborating with high-intellect colleagues and stakeholders across various functions and backgrounds
Effective interpersonal and communication skills, with a demonstrated ability to collaborate with partners across different functions, backgrounds, and levels of seniority
Quick learner, high curiosity; strong problem-solving and conceptual skills
Entrepreneurial, agile mindset; someone who wants to take part in building a world-class analytics organization