Client Data Analyst II

Acosta•Lewisville, TX

About The Position

The Client Data Analyst II partners with clients and internal teams to advance initiatives through strategy, analytics, and actionable insights. The role optimizes program measurement to support field team success, identifies areas where analytics can have the greatest impact, and uses relevant business and market information to support data-driven decisions and adapt tactics. The analyst also plays a key role in evolving, leading, and growing the data-driven discipline within the supported program. The position applies advanced statistical techniques and research methods to complex datasets, develops measurement frameworks and models, and turns findings into clear business recommendations. It collaborates with clients and cross-functional teams on optimization and go-to-market strategies, maintains current knowledge of analytical practices and industry trends, and supports measurement, research, and reporting through reproducible workflows and documentation. The position may involve client meetings, internal strategy sessions, and occasional field ride-alongs. Mosaic describes its desired workplace values as people minded, integrity, results oriented, trust, teamwork, innovation, and balance. Mosaic is an Equal Opportunity Employer and states that it will provide accommodations for persons with disabilities as required by law.

Requirements

Bachelor's degree in Statistics, Economics, Mathematics, Data Science, Analytics, Market Research, or a related quantitative field.
3–5 years of experience in analytics, consumer insights, market research, data science, or a related quantitative role.
Demonstrated experience applying statistical methods to business problems and influencing decision-making.
Experience designing and analyzing experiments, including A/B testing, test/control methodologies, multivariate testing, or other research designs.
Strong understanding of hypothesis testing, confidence intervals, sampling methodologies, significance testing, regression analysis, and model validation.
Proficiency in Python, R, SPSS, or other statistical software for data analysis, modeling, and research.
Intermediate to advanced SQL skills and experience working with large, complex datasets from multiple sources.
Strong data preparation skills, including cleaning, transformation, validation, and quality assurance.
Ability to turn complex analytical findings into actionable business recommendations and communicate them to technical and non-technical audiences.
Experience developing measurement frameworks, KPIs, and analytical methodologies to evaluate business performance.
Strong analytical thinking, intellectual curiosity, and problem-solving skills, including the ability to identify meaningful insights in large datasets.
Experience managing multiple projects and delivering high-quality work in a fast-paced and often ambiguous environment.
Intermediate to advanced Excel skills, including formulas, pivot tables, and data analysis functions.
Willingness to learn the business, understand client objectives, and identify opportunities for measurement, analytics, and strategic insights.

Nice To Haves

Experience with predictive analytics, forecasting, segmentation, driver analysis, or other advanced modeling techniques.
Experience with Power BI, Tableau, Looker, or other visualization tools for communicating insights and analytical results.
Remain informed about emerging analytical methodologies, market research techniques, consumer behavior trends, and industry best practices.

Responsibilities

Apply advanced statistical methods to complex datasets, identify business drivers, and develop actionable recommendations for clients and internal stakeholders.
Lead the development and evolution of measurement frameworks, KPIs, and analytical methodologies to evaluate program performance and business outcomes.
Design, execute, and interpret quantitative research, including market testing, A/B testing, multivariate experiments, and quasi-experimental analyses.
Build and validate statistical models to analyze customer behavior, sales performance, promotional effectiveness, and other business questions.
Conduct hypothesis testing, regression analysis, forecasting, segmentation, and other advanced analyses to support strategic decisions.
Translate analytical findings into business narratives that communicate insights, risks, assumptions, and recommendations to technical and non-technical audiences.
Partner with clients and cross-functional teams to identify optimization opportunities and develop data-driven go-to-market strategies.
Stay current on analytical best practices, emerging statistical methodologies, consumer insights research, and industry trends.
Collect, integrate, cleanse, transform, and validate complex datasets from multiple sources while maintaining data quality and integrity.
Develop reproducible analytical workflows and documentation for measurement, research, and reporting initiatives.
Participate in client meetings, internal strategy sessions, and occasional field ride-alongs to understand program operations and business objectives.
Use statistical and analytical software, including Python, R, SQL, and visualization tools, to conduct analyses and communicate results.