About Impact Analytics
Impact Analytics is an agentic-first AI software company transforming retail merchandising through cutting-edge AI, LLMs, and Generative AI technologies. As a fast-growing Series D company with deployments across five continents, it is building both industry-leading merchandising solutions and foundational AI agents that are redefining how retail decisions are made.
What makes Impact Analytics unique is its combination of deep retail domain expertise, strong innovation culture, and global presence. It is one of the few India-born AI companies recognized globally by organizations like Fortune, Gartner, and the Inc. 5000.
For candidates looking to work on next-generation AI products with global scale and real-world impact, Impact Analytics is an exciting place to build your career. Here’s a link to our website: www.impactanalytics.co.
The impact that you will be making
As a Lead AI Analyst, you will work at the intersection of data analytics, statistics, AI-driven insights, and product analytics. You will analyze complex datasets, develop analytical approaches, define meaningful business and product metrics, and translate data into recommendations that drive product and business outcomes.
The ideal candidate is highly proficient in Python and SQL, has a strong foundation in statistics and data modeling, and can independently solve ambiguous analytical problems while collaborating with Product, Engineering, Data Science, and business stakeholders.
What this role entails
- Lead end-to-end analytical projects, from problem definition and data exploration to solution development, validation, and business recommendations.
- Develop analytical solutions using Python and SQL to process, analyze, and interpret large and complex datasets.
- Apply statistical methods, hypothesis testing, regression analysis, and other data science techniques to solve business problems and validate findings.
- Analyze business and product performance to identify trends, patterns, anomalies, opportunities, and potential improvements.
- Define and track key performance indicators (KPIs), business metrics, and product metrics to measure outcomes and support decision-making.
- Perform product analytics, including funnel analysis, cohort analysis, customer segmentation, feature adoption, and performance measurement.
- Design, validate, and maintain analytical data models, ensuring data accuracy, consistency, and reliability.
- Work closely with Product, Engineering, Data Science, and business stakeholders to translate business requirements into scalable analytical solutions.
- Contribute to demand forecasting, business optimization, and other data-driven use cases where applicable.
- Explore and implement AI and Generative AI solutions to improve analytical workflows, productivity, and operational efficiency.
- Present complex analytical findings clearly and translate them into actionable business and product recommendations.
- Mentor team members, review analytical approaches and code quality, and establish best practices for data analysis and solution delivery.
What lands you in this role
- Strong hands-on proficiency in Python, including Pandas, NumPy, data manipulation, exploratory data analysis, and analytical problem-solving.
- Strong working knowledge of SQL, including complex joins, CTEs, window functions, aggregations, and query optimization.
- Solid understanding of statistics and data science fundamentals, including probability, hypothesis testing, confidence intervals, regression analysis, and experimental analysis.
- Good understanding of data modeling, data relationships, data granularity, fact and dimension tables, and data warehousing concepts.
- Experience in product analytics, business analytics, or data science-driven problem-solving.
- Ability to define meaningful metrics, interpret analytical results, and connect findings to business outcomes.
- Strong logical reasoning, structured thinking, and critical-thinking skills.
- Experience working with large datasets and data visualization or reporting tools such as Tableau, Power BI, or equivalent.
- Ability to communicate complex technical concepts to business and non-technical stakeholders.
- Experience leading analytical projects, mentoring team members, or driving analytical quality and best practices.
- Strong ownership, attention to detail, and the ability to work independently in a fast-paced, cross-functional environment.
Preferred Qualifications
- Experience in AI/ML-driven products, SaaS, retail analytics, e-commerce, consumer goods, or demand forecasting.
- Familiarity with retail business processes, merchandising, pricing, promotions, or supply chain analytics.
- Exposure to cloud data platforms such as Snowflake, BigQuery, or Redshift.
- Familiarity with Generative AI applications and opportunities to improve analytical productivity.
- Experience working in product-focused organizations and collaborating closely with Product and Engineering teams.
What we offer
- An opportunity to be part of some of the best enterprise SaaS products to be built out of India.
- Opportunities to quench your thirst for problem-solving, experimenting, learning, and implementing innovative solutions.
- A flat, collegial work environment, with a work hard, play hard attitude.
- A platform for rapid growth if you are willing to try new things without fear of failure.
- Remuneration with best-in-class industry standards with generous health insurance cover
Our accolades include:
- Ranked as one of America's Fastest-Growing Companies by Financial Times for five consecutive years: 2020-2024.
- Ranked as one of America's Fastest-Growing Private Companies by Inc. 5000 for seven consecutive years: 2018-2024.
- Voted #1 by more than 300 retailers worldwide in the RIS Software LeaderBoard 2024 report.
- Ranked #72 in America’s Most Innovative Companies list in 2023—by Fortune—alongside companies like Microsoft, Tesla, Apple, IBM, etc.
- Forged a strategic partnership with Google to equip retailers with cutting-edge generative AI tools.
- Recognized in multiple Gartner reports, including Market Guides and Hype Cycle, spanning assortments, merchandising, forecasting, algorithmic retailing, and Unified Price, Promotion, and Markdown Optimization Applications.