Job Summary

Role: Manager - Analytics Intelligent Automation

Experience: 8 to 12 Years

Job Location: Chennai

Role Overview

The Analytics Manager will play a vital role in bridging data-driven insights with business strategy to enhance customer experience, optimize marketplace operations, and drive process automation. This is a hybrid leadership role requiring a strong foundation in classical statistical modelling, financial dashboarding, and the orchestration of cutting-edge Generative AI (GenAI) and LLM-driven workflow automation.

Key Responsibilities

- GenAI Process Automation Orchestration: Oversee the development and deployment of LLM-powered systems, multi-agent architectures, and automated customer support workflows. Manage the systematic transition of operational workflows from legacy web-scraping dependencies to secure, high-uptime API configurations.
- Customer Insights Text Analytics: Analyze customer buying behaviors and transaction histories. Oversee unstructured data mining pipelines (customer review analysis, negative feedback loops, and automated support ticket mapping) using NLP and semantic clustering to improve service recovery and retention.
- Advanced Demand Forecasting: Build and optimize multi-level forecasting models (including ARIMA, Prophet, and mixed-effects time-series frameworks) that incorporate energetic regressors like marketing ad spend, inventory stockouts, and seasonal marketplace anomalies to safeguard supply chain health.
- Marketplace Pricing Dynamics Buy Box Analysis: Supervise continuous marketplace price-monitoring and experiment engines. Drive statistical and regression analyses to evaluate price/delivery window elasticity, benchmarking internal merchant metrics against external competition to maximize Buy Box ownership.
- Operations Customer Service KPI Analytics: Monitor internal agent productivity, system exception triggers, and operational SLAs.



Maintain oversight over the validation pipelines tracking financial metrics like marketplace remittance data, settlement reconciliation, and margin/chargeback tracking.
- Cross-Channel Website Analytics: Track user navigation paths, conversion rates, sessions, and marketing attribution patterns across internal sites and external retail portals (Amazon, Wayfair, Walmart, etc) to isolate drivers of commercial performance.
- Reporting Data Infrastructure Governance: Oversee the teams Power BI enterprise reporting layer and data workflows. Champion performance optimizations (such as data-prep caching and migrating legacy processing loops to faster computational frameworks) to minimize dashboard latency and secure reliable data auto-refreshes.

Required Knowledge Technical Skills

1. Core Analytics, Data Engineering Reporting

- Languages: Python and advanced SQL Server development.
- Data Processing Libraries: Expert-level knowledge of data manipulation toolsets, with a strong emphasis on high-performance frameworks like Polars or optimized Pandas for processing massive (gigabyte-scale) datasets.
- Business Intelligence: Mastery of Power BI architecture, including advanced Data Analysis Expressions (DAX), Power Query data-modeling, and row-level security logic. Experience building lightweight data applications via Streamlit or HTML interfaces is highly valued.

2. Advanced Modeling Statistical Data Science

- Statistical Modeling: Hands-on experience with predictive modeling frameworks, including Ordinal Logistic Regression, mixed-effects time-series analysis.



Knowledge of other advanced statistical modelling methods and optimization methods will be an advantage

3. GenAI, Large Language Models (LLMs) Process Automation

- LLM Orchestration: Practical experience building and tuning production-grade GenAI pipelines using commercial and open-source models (eg, Gemini via Vertex AI, Llama).
- Prompt Engineering Cost Optimization: Proven experience implementing cost-efficient model deployment strategies, including Prompt Caching and localized token-filtering guardrails.
- Workflow Automation Scraping Architecture: Working knowledge of automation platforms like n8n (integrating Model Context Protocol/MCP tools) and enterprise task schedulers like Apache Airflow. Familiarity with headless browser frameworks (Playwright or Selenium) and proxy management protocols is a major advantage.
- Vector Databases: Exposure to semantic search architectures and vector databases (such as Qdrant or similar embedded indexing environments) for text and entity mapping.

Behavioral Leadership Competencies

- Hybrid Technical Leadership: Proven track record managing teams across concurrent data science, dashboard engineering, and software automation sprints.
- Clear, Efficient and Actionable Communication: Exceptional ability to translate complex data model outputs / analyses and algorithmic behaviors into crisp, high-level tactical briefs for senior executive stakeholders.
- Agile Problem Solving: A detail-oriented, iterative mindset capable of diagnosing root-cause of problems such as data anomalies, system timeouts, or pipeline bottlenecks etc under tight operational windows.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Manager - Analytics (Chennai)
🏢 OJCommerce
📍 Chennai