Senior Manager, Data & Analytics Strategy

dentsu

1d•$94,000 - $115,000•Remote

About The Position

Merkle is a leading data-driven, technology-enabled, global performance marketing agency specializing in the delivery of unique, personalized customer experiences across platforms and devices. For more than 30 years, Fortune 1000 companies and leading nonprofit organizations have partnered with Merkle to maximize the value of their customer portfolios. The agency's heritage in data, technology, and analytics forms the foundation for its unmatched skills in understanding consumer insights that drive people-based marketing strategies. Its combined strengths in performance media, customer experience, customer relationship management, loyalty, and enterprise marketing technology drive improved marketing results and competitive advantage. With over 9,000 employees worldwide across locations in US, EMEA and APAC, Merkle is part of the Dentsu Aegis Network. For more information, visit www.merkle.com. As Senior Manager of Data & Analytics Strategy, you'll deliver analytics solutions and measurement strategies for client programs, transforming complex data into clear, actionable insights that support business growth. Working as an individual contributor with a focus at the intersection of promotions, CRM, and loyalty, you'll collaborate with cross-functional teams to implement measurement frameworks, execute analytics projects, and deliver reporting and data-driven recommendations that strengthen client performance. This role offers the opportunity to contribute to analytics initiatives while supporting client relationships, ensuring the data strategy aligns with client business objectives to create meaningful impact on how global brands connect with their customers.

Requirements

3+ years in data science/analytics roles delivering campaign measurement, predictive analytics, and business recommendations
Balanced combination of Analytics, Strategy and Business Consulting skills
Bachelor's or master's degree in quantitative field (STEM, business, finance, marketing)
Proven ability to solve business problems with data and identify key performance levers
Proficiency analyzing transaction-level data from large databases
Hands-on experience with cloud-based big data platforms such as Redshift, BigQuery, Teradata, Snowflake, or Databricks
Hands-on experience with modern CRM platforms such as Salesforce and/or Braze
Strong data storytelling and presentation abilities
Solid task prioritization, time management, and cross-functional collaboration skills
Experience designing and executing A/B testing programs and marketing experiments
Ability to translate complex analytics into actionable business insights
Demonstrated ability to break work into clear tasks and work across technical and business domains

Nice To Haves

Experience in loyalty analytics preferred
Familiarity with predictive modeling approaches including clustering, regression, ensemble modeling, and decision trees
Experience with machine learning libraries (NumPy, scikit-learn) is a plus
Experience with visualization tools (Tableau, Power BI) preferred
Knowledge of digital marketing ecosystem and analytics platforms (Amplitude, Adobe, GA)
Track record building effective reports and dashboards
Experience using AI to drive efficiency and scale or augment analysis efforts is a plus

Responsibilities

Deliver measurement strategies and reporting that align with client objectives
Participate in client meetings to document program goals and define metrics and KPIs
Present findings in clear, actionable ways that support decision-making and improvement
Execute analytics projects from problem identification through solution delivery
Brief, orchestrate, and oversee technical analytics work by offshore and third-party teams
Conduct data analysis using statistical techniques to analyze experiments and user behavior
Identify gaps and challenges in data collection and develop viable approaches to address them
Provide subject matter expertise in measurement, analysis, and data-driven solutions
Develop learning agendas that identify opportunities to use data to inform new marketing tactics
Support innovation in experimental design and marketing testing programs
Partner with other disciplines to refine, optimize, and support recommendations