Job Description

Key Responsibilities Define Analytics & AI Vision & Strategy: Set the vision, define key business and product metrics, and align stakeholders Develop measurement frameworks, establish AI/ML-driven insights, and ensure data quality. Identify opportunities for AI-driven automation and predictive modelling. Drive AI & Data-Backed Business Insights: Identify and decode patterns in sales, revenue, customer experience, and financial operations (billing, collections, payments) using AI-powered forecasting and anomaly detection. Apply machine learning models to improve lead-to-revenue conversion, optimize sales cycles, and reduce churn. Experiment with Generative AI tools to enhance analytics storytelling, automate reporting, and create personalized insights for stakeholders. Own End-to-End AI & Analytics Execution: Work hands-on with data teams to define ML-driven hypotheses, run experiments, and measure impact. Ensure AI-driven analytics is embedded from day 0 in product and business initiatives. Identify key business problem statements, break them down into AI-powered analytics solutions, and drive clarity across functions. Communicate AI-Driven Insights with Impact: Translate complex AI and machine learning insights into clear, compelling, and actionable stories for senior leadership. Evangelize AI and ML-driven decision-making, ensuring business and product teams harness AIs full potential. Cross-Functional Collaboration & AI Readiness: Work closely with sales, marketing, experience, product, and data teams to drive AI-powered analytics initiatives. Partner with engineering and data science teams to build scalable AI and ML solutions. Stay at the forefront of AI/ML advancements, evaluating LLMs, Generative AI, and predictive modelling frameworks for business intelligence. Preferred Qualifications Experience: 10+ years in analytics, with at least 4+ years leading a team of 10+ members in a senior role. Business Knowledge: Strong understanding of B2B sales cycles, revenue models, customer journey mapping, pricing, billing, and collections. Deep knowledge of business KPIs, including lead conversion, order booked, revenue, churn, billing, collection and financial performance indicators. AI & ML Expertise: Hands-on experience with AI/ML algorithms, Generative AI, and predictive analytics for business decision-making. Strong proficiency in Python, PySpark, TensorFlow, Scikit-Learn, or similar AI/ML tools. Experience deploying machine learning models for revenue forecasting, churn prediction, and anomaly detection. Ability to leverage LLMs (like GPT, Claude, or Gemini) to automate reporting, insights generation, and customer analytics. Technical & Data Analytics Skills: Data Strategy & Governance: Ability to define frameworks, set standards, and ensure compliance with data regulations. Advanced Analytics: Proficiency in A/B testing, cohort analysis, MECE methodologies, and predictive modeling. Data Infrastructure: Understanding of ETL pipelines, data warehousing, and cloud-based AI analytics platforms. Data Visualization: Expertise in BI tools (Tableau, Power BI, Looker) to tell compelling stories. Problem Solving & Storytelling: Ability to break down complex AI problems into structured analysis and change approach when needed. Strong storytelling skills, making AI insights accessible and actionable for business leaders. Leadership & AI Evangelism: Track record of building and scaling AI-driven analytics teams. Proven ability to engage stakeholders at all levels, evangelizing AI-driven business transformation.