DESCRIPTION Mosaic is a leading North American Integrated Marketing Agency, specialized in connecting with consumers through Experiential Marketing, B2B, Sales & Merchandising, and Shopper Marketing. At Mosaic, we are never satisfied with the status quo and are in constant search for new ideas and current ways to help our clients build their brands amidst the evolving dynamics of empowered consumers and leveraging new technologies. The Client Data Analyst II (analyst) position is responsible for partnering with our clients and teams to drive their initiatives with strategy, analytics and actionable insights, optimizing program measurement to drive field team success, and constantly engaging with the team to better understand where they can have the greatest impact. The analyst will leverage business and market relevant information to make data-driven decisions that allow Mosaic to achieve its sales and marketing objectives and quickly adapt tactics. The analyst will play a key role in evolving, leading, and growing the data-driven discipline within the program they support. The Incumbent(s) in this position should exhibit the following values: People Minded

– Must show dignity and respect to all people

Integrity

– Must exemplify the highest degree of ethical behavior

Results Oriented

– Must show passion, pride and commitment to succeed

Trust

– Must be honest, sincere and confident

Teamwork

– Must build trusting relationships

Innovation

– Must progress through a combination of creativity, common sense and vision

Balance

– Must maintain an optimistic attitude and keep perspective on what is important in life

RESPONSIBILITIES

Apply advanced statistical methods to analyze 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 studies, including market testing, A/B testing, multivariate experiments, and quasi-experimental analyses.

Build and validate statistical models to understand customer behavior, sales performance, promotional effectiveness, and other key business questions.

Conduct hypothesis testing, regression analysis, forecasting, segmentation, and other advanced analytical techniques to support strategic decision-making.

Translate analytical findings into compelling business narratives, communicating insights, risks, assumptions, and recommendations to both technical and non-technical audiences.

Partner with clients and cross-functional teams to identify opportunities for optimization 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 large, complex datasets from multiple sources while ensuring data quality and integrity.





Develop reproducible analytical workflows and documentation to support ongoing measurement, research, and reporting initiatives.

Participate in client meetings, internal strategy sessions, and occasional field ride-alongs to maintain a strong understanding of program operations and business objectives.

Utilize statistical and analytical software such as Python, R, SQL, and visualization tools to conduct analyses and communicate results.

QUALIFICATIONS

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 solve business problems and influence decision-making.

Experience designing and analyzing experiments, including A/B testing, test/control methodologies, multivariate testing, or other research designs.

Strong understanding of statistical concepts including 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 applications.

Intermediate to advanced SQL skills and experience working with large, complex datasets from multiple sources.

Experience with predictive analytics, forecasting, segmentation, driver analysis, or other advanced modeling techniques preferred.

Strong data preparation skills, including data cleaning, transformation, validation, and quality assurance.

Ability to translate com

📌 Client Data Analyst II (Mississauga)
🏢 Acosta
📍 Mississauga