Designation : Manager
Level : L4
Location : Chennai, Tamil Nadu , India
Experience : 8 to 12 Years
Job Role :
Experience: 8–12 years of core analytics experience, with at least 3+ years in a leadership/client-facing manager role (Fintech or Banking experience highly preferred).
AI & Technical Stack:
Proficiency in SQL, Python, or R.
Deep experience with AI/ML techniques (Predictive Modeling, Clustering, NLP, or Generative AI integrations) used in daily problem-solving.
Hands-on familiarity with BI & Data tools (Tableau, PowerBI, Databricks, Snowflake, BigQuery, Amplitude, Mixpanel, etc.).
Client & Communication Mastery: Flawless verbal and written communication skills with a proven track record of managing and presenting to global (US/UK/EU) stakeholders.
Business Acumen: Demonstrated ability to drive commercial growth, craft client proposals (RFP/pitches), and convert insights into revenue opportunities.
Education: Bachelor’s or Master’s degree in Data Analytics, Computer Science, Statistics, Mathematics, Economics, or an MBA from a top-tier institute.
Responsibilities :
Key Responsibilities
1. Problem Solving & Technical Leadership
Translate complex, ambiguous client business challenges into structured analytics frameworks, technical solutions, and actionable AI roadmaps.
Apply AI and Machine Learning natively into daily analytics workflows, automation routines, and client deliverables.
Deliver hands-on analytical work while reviewing team deliverables to ensure technical accuracy, business context, and high presentation quality.
2. Domain Expertise (1+ Core Areas)
Lead analytics strategy across at least one or more key Fintech functions:
Marketing Analytics: Customer Acquisition Cost (CAC), Campaign Optimization, Multi-Touch Attribution, LTV Modeling.
Sales Analytics: Conversion Funnels, Sales Force Effectiveness, Pipeline Analytics, Cross-sell/Up-sell strategies.
Product Analytics: User Behavior Analysis, Feature Adoption, A/B Testing, Churn Prediction, Onboarding Funnel Optimization.
Risk Analytics: Fraud Detection, Credit Scoring Models, Underwriting Analytics, Portfolio Risk Monitoring.
3. Client Management & Account Growth
Serve as the primary offshore liaison, building deep trust and maintaining fluent, impactful communication with senior executive stakeholders.
Cross-pollinate ideas: Transfer best practices, successful frameworks, and innovative use cases across different business units within the client organization.
Proactively identify whitespace opportunities, draft compelling solution pitches, and partner with onshore leadership to expand LatentView's foot-print within the account.
4. Team Mentorship & Delivery Management
Lead, mentor, and upskill a high-performing team of data scientists and analytics consultants.
Drive delivery excellence, ensuring timelines, resource allocation, and quality standards meet client expectations.
Required skills :
Proficiency in SQL, Python, or R. Deep experience with AI/ML techniques (Predictive Modeling, Clustering, NLP, or Generative AI integrations) used in daily problem-solving. Hands-on familiarity with BI & Data tools (Tableau, PowerBI, Databricks, Snowflake, BigQuery, Amplitude, Mixpanel, etc.).