Analytics Lead Digital Client Acquisition

Job Description — Lead – Analytics

Role Title: Analytics Lead – Digital Client Acquisition

Location: Mumbai, India

Reporting To: Head – Digital Client Acquisition

Type: Full‑time

Role Objective

We are seeking a highly skilled Analytics Lead to drive data‑driven decision making across customer acquisition, trading behavior, and lifecycle management. The role requires strong hands‑on expertise with modern analytics tools, combined with leadership ability to build frameworks and influence senior stakeholders.

Key Responsibilities

• Analytics Strategy:

Define and execute analytics roadmap aligned with business goals (acquisition, retention, ROI).

• Data Visualization:

Build dashboards and reports using Tableau, Power BI, and other BI tools for management insights.

• Customer Lifecycle Analytics:

Analyze onboarding, drop‑offs, trading activity, churn, and lifetime value.

• Product & Trading Insights:

Deliver insights on F&O, equities, and digital trading journeys to improve adoption.

• Advanced Analytics:

Apply statistical models, segmentation, and predictive analytics to identify growth opportunities.

• Team Leadership:

Mentor analysts, establish best practices, and ensure high‑quality delivery.

• Cross‑functional Collaboration:

Partner with marketing, product, and sales teams to embed analytics into decision making.

Required Skills & Experience

• Strong expertise in Tableau, Power BI, SQL, Python/R.
• Experience with data warehousing tools (Snowflake, Big Query, Redshift).
• Knowledge of capital markets, broking products, F&O trading, PMS/AIF.
• Ability to translate complex data into actionable business insights.
• Strong communication skills for presenting to senior management.

Preferred Background

• 8–12 years of analytics experience, with at least 3–4 years in a leadership role.
• Prior exposure to broking/wealth management domain is highly desirable.
• Experience in digital acquisition analytics, ROI measurement, and customer lifecycle management.

Education

• Bachelor's/Master's in Engineering, Statistics, Economics, or related field.
• Certifications in BI tools or data science preferred.