Senior Analyst, Data Science - Temporary Worker

dentsu•San Francisco, NY

9d•Hybrid

About The Position

Dentsu’s Data Science team develops robust, actionable solutions to advance clients’ business goals and supports decision-making through customer analytics expertise. The Senior Analyst applies advanced statistical and data engineering methods to customer analytics and leads projects through completion. The position is temporary for approximately 12 months, based in the San Francisco Bay Area or New York, with a hybrid arrangement requiring three days in the office. The listed start date is ASAP. The role leads campaign measurement and experimentation, develops audience insights, and translates analytical findings into recommendations for campaign strategy, media optimization, and investment. It also builds scalable models, dashboards, reporting tools, AI-enabled automations, and measurement infrastructure, while partnering with cross-functional teams and sharing research on methodologies and tools that improve analytical quality and marketing effectiveness.

Requirements

Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Computer Science, or Data Science, or equivalent practical experience.
At least 3 years of experience in data science, analytics, or a related quantitative role.
Advanced SQL skills and experience querying, analyzing, and validating large datasets.
Proficiency in Python or R and experience with relevant analytical and visualization libraries; Python examples include pandas, NumPy, statsmodels, scikit-learn, and Matplotlib.
Strong knowledge of statistical methods, including regression, hypothesis testing, experimental design, and causal inference, with hands-on experience designing and analyzing A/B tests and measuring marketing impact.
Experience building and maintaining data pipelines and analytical datasets using SQL and Python, including data integration, transformation, validation, and automated reporting.
Ability to independently manage cross-functional stakeholder relationships, communicate progress and risks proactively, and explain complex findings as clear recommendations to non-technical audiences and leadership.
Experience using AI tools such as Claude for coding, analysis, automation, and analytical tool development, with careful validation of generated outputs.

Nice To Haves

Familiarity with geo experiments, brand lift studies, survey analysis, or marketing mix modeling.

Responsibilities

Define marketing goals, success metrics, learning agendas, and measurement strategies, translating business questions into clear analysis plans.
Own campaign measurement from pre-launch planning through in-flight monitoring and post-campaign evaluation; identify performance issues and recommend optimizations.
Design, execute, and analyze A/B tests, holdout tests, geo experiments, and brand lift studies, including hypothesis development, success metrics, sample-size and power calculations, test validation, and recommendations.
Integrate consumer sentiment, survey responses, and behavioral data to develop audience insights that inform targeting and messaging.
Translate findings into recommendations on campaign strategy, media optimization, and investment; guide stakeholders in interpreting results and applying insights to business decisions.
Develop scalable models, dashboards, reporting tools, AI-enabled automations, and measurement infrastructure for multiple campaigns and evolving business needs.
Drive analytical tool development from scoping and brainstorming through prototyping and deployment.
Partner with marketing, media, research, growth, product, and data engineering teams to prioritize opportunities, align delivery plans, and present recommendations to leadership.
Lead focused research and knowledge-sharing initiatives, evaluating methodologies and tools that improve analytical quality, efficiency, and marketing effectiveness.