Senior Data Analyst, CRM

David Yurman•New York, NY

2d•$110,000 - $120,000•Hybrid

About The Position

The Senior Data Analyst is responsible for leveraging data to provide insights that drive customer understanding, segmentation, and business growth. In this role, you will work closely with cross-functional teams (Finance, Ecom, Marketing & CRM) to analyze customer behavior, improve customer engagement, and optimize marketing strategies. You will be tasked with ensuring data integrity, building a combination of templated and ad hoc reports in support of our cross functional partners and offering actionable insights to enhance customer experiences and drive business outcomes.

Requirements

Minimum 4-6+ years of experience in data analytics or a related field, with a focus on customer behavior and segmentation.
Proven experience working with large, complex datasets, preferably in omnichannel retail
Technical Skills: Strong proficiency in SQL for data querying and manipulation. Advanced skills in Excel for analysis, reporting, and modeling. Experience with data visualization tools like Tableau, Sigma, Power BI, or Looker. Experience with GA4, Medallia, YouGov, Snowflake, 3rd party customer data
Familiarity with CRM platforms (Salesforce, HubSpot, etc.) and customer data platforms (CDPs)
Knowledge of statistical modeling techniques, such as regression analysis, time series analysis, and predictive modeling with a test and learn, agile testing mentality framework.
Analytical Skills: Strong problem-solving abilities with a focus on actionable insights and business outcomes.
Communication Skills: Excellent written and verbal communication skills to present findings to both technical and non-technical stakeholders.
Attention to Detail: Strong attention to data accuracy, quality control, and the ability to spot trends and anomalies in datasets.
Experience in customer segmentation, campaign performance analysis, and customer lifetime value (CLTV) modeling.
Familiarity with A/B testing frameworks and experimental design.
Experience working with marketing teams on personalization, targeting, and customer engagement strategies.
Knowledge of data privacy regulations such as GDPR, CCPA, and how they impact customer data practices
Data-Driven: Ability to make decisions based on data insights and analytics, with a strategic mindset.
Collaboration: Work cross-functionally with various teams, including marketing, product, and sales, to deliver data insights and recommendations.
Adaptability: Thrive in a fast-paced, evolving environment, adjusting to new challenges and emerging tools or technologies.
Bachelors degree in Marketing, Data Science, Mathematics, Statistics or related field

Responsibilities

Customer Growth Model – Maintain and optimize existing model
Brand Heath Metrics: own YouGov structure and all associated reporting and insights
Customer Journey Analysis: Work with marketing, eComm, CRM, and product teams to map and analyze customer journeys across various touchpoints, identifying pain points and opportunities to enhance the customer experience.
Campaign Performance Tracking: Collaborate with the marketing team to measure and report on the performance of marketing campaigns, assessing their impact on customer acquisition, engagement, and retention.
Advanced Analytics & Machine Learning: Analyze large datasets to extract actionable insights and recommendations from data mining, segmentation, customer profiling and quantitative analysis. Provide regular reports on customer segments, CLTV, and other key performance indicators. Work closely with business partners to integrate and operationalize the recommendations in the business strategies, plans and tactics. Work with Data Science teams to identify opportunities for advanced analytics and machine learning that drive better customer understanding and performance.
Data Visualization: Develop clear, concise, and actionable dashboards and reports using visualization tools like Tableau, Power BI, Looker or Sigma, presenting complex data in an understandable format for stakeholders.
Market Research & Insights: Utilize customer data to support market research efforts, competitive analysis, and consumer insights projects.
Data Integrity & Governance: Ensure data accuracy and completeness by identifying and addressing data quality issues. Maintain best practices for data hygiene, validation, and governance in collaboration with IT and Data Engineering teams.
Collaboration & Cross-Functional Projects: Partner with teams in marketing, product, ecommerce, and sales to align customer data insights with broader business strategies. Contribute to the development of personalization strategies.