Staff Data Scientist

Location: Worldwide (Remote/Hybrid) Reports to: TBD

About CINC Systems CINC Systems is the largest provider of accounting and management software in the community association management industry and the innovator behind accounting and banking integration. Founded in 2005 by a banker as the industry’s first SaaS offering, CINC Systems now employs nearly 400 people and provides software and applications to more than 50,000 associations servicing over 5 million doors.

In January of 2024, Hg Capital made a significant investment in CINC to accelerate the company’s growth trajectory and institute rapid product development.

At CINC, innovation drives our growth, and our people sustain it. We are proud of our humble, accountable, and team-oriented culture, and we are committed to building products and a workplace that create long term value for our customers and our team.

About The Role The Staff Data Scientist is a senior individual contributor responsible for advanced data analysis, feature exploration, model design, and research that enable the discovery of new insights and product opportunities. This role focuses on understanding data deeply, experimenting with models, and translating analytical findings into clear recommendations that inform product, engineering, and business decisions.

This is not a reporting or dashboarding role. It is a research-oriented, insight-driven role for someone who thrives on ambiguity, asks sharp questions, and uses data to illuminate what should be built next and why.

Key Responsibilities

• Explore large, complex datasets to uncover patterns, anomalies, and opportunities
• Design and evaluate statistical and machine learning models to support insight discovery and hypothesis testing
• Partner with product, engineering, and business stakeholders to frame questions and translate findings into actionable insights
• Conduct feature exploration and selection to inform downstream AI and analytics initiatives
• Design experiments and analyses to validate assumptions and measure impact
• Develop prototypes and proofs of concept that demonstrate the potential value of new models or approaches
• Communicate results clearly through narratives, visualizations, and written recommendations
• Stay current with advances in data science, statistics, and applied machine learning
• Collaborate with Data Engineering and AI Engineering teams to transition validated ideas into production-ready work
• Mentor other data scientists and analysts, raising the level of analytical rigor across the organization

Qualifications Technical Expertise

• 10+ years of experience in data science, applied research, or advanced analytics roles
• Strong foundation in statistics, probability, and experimental design
• Experience designing and evaluating machine learning models for classification, regression, clustering, or forecasting
• Proficiency in Python and common data science libraries
• Experience working with large datasets in SQL-based and analytical data environments
• Ability to reason about data quality, bias, and limitations

Research and Collaboration

• Proven ability to work in ambiguous problem spaces and define meaningful analytical questions
• Strong communication skills, able to explain complex findings to non-technical audiences
• Experience influencing product or business strategy through data-driven insights
• Comfortable collaborating across disciplines without formal authority
• Structured thinker who can balance exploration with rigor

Mindset and Values

• Deep curiosity and a passion for discovery
• Belief that insights precede automation and that not every problem needs a model
• Learning-first attitude, continuously improving methods and tools
• Pragmatic and outcome-oriented, focused on decisions and impact
• Respects the difference between research, engineering, and operations while collaborating closely with all three

What Success Looks Like

• New insights lead directly to product opportunities, experiments, or strategic decisions
• Models and analyses are trusted, well-reasoned, and reproducible
• Stakeholders understand not just the results, but the implications and trade-offs
• Promising ideas move efficiently from discovery to validation and into engineering roadmaps
• The Staff Data Scientist is recognized as a thought partner and expert across the organization

CINC is an Equal Opportunity Employer of women, minorities, protected veterans and individuals with disabilities.