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Staff Data Scientist
- New York, New York, United States
- New York, New York, United States
Über
Location: Worldwide (Remote/Hybrid) Reports to: TBD
Staff Data Scientist About CINC Systems CINC Systems is the leading provider of accounting and management software for the community association management industry. Our platform supports tens of thousands of associations and millions of homes, generating rich datasets across finance, operations, and customer interactions. As CINC evolves toward more intelligent, AI-enabled products, deep analytical insight and rigorous data science are critical to identifying new opportunities, shaping product strategy, and validating where AI can deliver real value. The Staff Data Scientist plays a central role in that discovery.
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
Seniority level Mid-Senior level
Employment type Full-time
Job function Engineering and Information Technology
Industries Software Development
CINC is an Equal Opportunity Employer of women, minorities, protected veterans and individuals with disabilities.
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Sprachkenntnisse
- English
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