CRM Analytics Manager

eBay

7 - 12 years

7 Lacs

bengaluru

Posted:2 hours ago| Platform:

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Skills Required

automation version control orchestration data modeling machine learning data visualization analytics sql crm python

Work Mode

Work from Office

Job Type

Full Time

Job Description

What you ll do

Achieve tangible results. Establish benchmarks and learning goals; develop structures that link campaign performance to business results, CLV, retention.
Advance personalization with ML/AI. Develop or partner on models (propensity, churn, next-best action, send-time/content optimization, uplift modeling) and integrate them into CRM decisioning and orchestration.
Lead experimentation at scale. Build and run A/B and multivariate tests; apply sound statistical methods (power analysis, capping, sequential testing, causal inference) to produce trustworthy results.
Develop robust analytics. Use SQL/Python for data modeling and reproducible pipelines; compose self-serve datasets and dashboards to accelerate decision-making.
Optimize channel strategy. Evaluate email, push, in-app, onsite, and lifecycle programs; recommend frequency, targeting, and creative strategies grounded in data.
Tell the story. Translate complex analysis into clear, actionable recommendations for senior collaborators; influence roadmaps and CRM evolution.
Improve the craft. Guide analysts, advocate for guidelines in documentation, code review, and experimentation hygiene; promote an inclusive, growth-focused culture.
Safeguard data use. Partner with Legal/Privacy to ensure compliance (e.g., GDPR), guardrails, and responsible AI practices.

Qualifications

Hands-on CRM analytics experience delivering impact in a consumer or marketplace context.
Machine-learning AI experience applied to CRM/personalization (e.g., propensity, churn, LTV/CLV modeling, recommendation/next-best action, uplift).
Experimentation statistics expertise, including test building, sample sizing, variance reduction, and causal inference.
SQL and Python proficiency for data wrangling, modeling, and automation; familiarity with data warehouses and version control.
Dashboarding data visualization skills (Tableau preferred) to build clear, credible self-serve insights.
Business sense proven through translating insights into strategies that yield measurable outcomes.
Communication collaborator leadership across Marketing, Product, and Engineering; ability to influence at executive level.

Nice to have

Experience with marketing tech stacks (contact strategy decisioning/orchestration, unified data platforms, experimentation platforms) and event-level data.
Familiarity with Spark/Databricks, Airflow, or similar for scalable pipelines.
Knowledge of generative AI applications for CRM content/testing and guardrail development.
Marketplace or two-sided platform experience.

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