Senior Data Analysts

CCC Intelligent Solutions

7d•Remote

About The Position

CCC Intelligent Solutions Inc. (CCC) is a leading cloud platform for the multi-trillion-dollar insurance economy, creating intelligent experiences for insurers, repairers, automakers, part suppliers, and more. At CCC, we’re making life just work by empowering more than 35,000 businesses with industry-leading technology to get drivers back on the road and to health quickly and seamlessly. We’re pushing boundaries with innovative AI solutions that simplify and enhance the claims and repair journey. Through purposeful innovation and the strength of its connections, CCC technologies empower the people and industry relied upon to keep lives moving forward when it matters most. Learn more about CCC at www.cccis.com. The Role Key Responsibilities: Senior Data Analysts for various and unanticipated worksites throughout the U.S. (HQ: Chicago, IL). Use mathematics and logic to support the decision-making of leadership team in high stake data situations. Consult with internal and external clients to resolve data science problems. Serve as analytics expert using data and models. Deliver client-facing analytics solutions including developing statistical models and optimization tools. Answer ambiguous open-ended questions with clear data-driven insights and recommendations. Uncover new product research directions (hypothesis generation). Create data insights by helping define and build the sales and marketing narrative. Build, own, and standardize client-facing analysis and reporting on mature products. Work closely with ML team to analyze the impact of modeling results, debug data issues, and communicate findings to colleagues and clients. Write relational database queries, write design documents, write code for reproducible analytics, perform code reviews, and maintain state-of-the-art engineering practices. Grow and learn in data and Machine Learning (ML) space. Oversee integration of cross-organizational projects, drive improvements. Communicate including through storytelling, and present findings to internal and external stakeholders. Technical Environment: data analysis/quantitative, Machine Learning and Product environments; statistics, linear & non-parametric models, advanced SQL engineering; Bayesian statistics, causal inference methods; A/B and multi-arm experiments; Python, pandas, Jupyter notebooks, and SQL-based analytics dashboards (e.g., data studio), standard statistical packages and visualization tools; Product and Business analytics, fundamentals, and processes; reproducible analytics pipelines; market-ready graphs, slides, figures, and presentations. #LI-DNI #NOINDEED

Requirements

Master’s degree in Data Science or Analytics or Computer Engineering or any Engineering or related field plus 2 years of experience with data analysis/quantitative experience with Machine Learning or as a Data Scientist or Researcher required.
Must have previous data analysis/quantitative experience within Machine Learning and Product environments
Experience delivering client-facing analytics solutions including developing statistical models and optimization tools
Expertise with statistics, linear & non-parametric models, & advanced SQL engineering
Experience with written production quality code for reproducible analytics pipelines, expertise with Python, pandas, Jupyter notebooks, SQL-based analytics dashboards (data studio), standard statistical packages and visualization tools
Data illustrator skills, including market-ready graphs, slides, figures, and presentations
Proven experience with Product and Business analytics, fundamentals, and processes, and synthesizing data insights into actionable recommendations
Excellent communication, storytelling, and presentation skills.
Telecommuting permitted.
(Bachelor’s degree in Data Science or Analytics or Computer Engineering or any Engineering or related field plus 5 years of progressive experience with data analysis/quantitative experience with Machine Learning or as a Data Scientist or Researcher also acceptable.)

Responsibilities

Use mathematics and logic to support the decision-making of leadership team in high stake data situations.
Consult with internal and external clients to resolve data science problems.
Serve as analytics expert using data and models.
Deliver client-facing analytics solutions including developing statistical models and optimization tools.
Answer ambiguous open-ended questions with clear data-driven insights and recommendations.
Uncover new product research directions (hypothesis generation).
Create data insights by helping define and build the sales and marketing narrative.
Build, own, and standardize client-facing analysis and reporting on mature products.
Work closely with ML team to analyze the impact of modeling results, debug data issues, and communicate findings to colleagues and clients.
Write relational database queries, write design documents, write code for reproducible analytics, perform code reviews, and maintain state-of-the-art engineering practices.
Grow and learn in data and Machine Learning (ML) space.
Oversee integration of cross-organizational projects, drive improvements.
Communicate including through storytelling, and present findings to internal and external stakeholders.