Tanoy Dewanjee is a seasoned decision science professional with a decade of experience across various industries, specializing in leveraging data analytics to drive business value. His career is marked by a commitment to embedding fact-based decision-making into core business systems and promoting a data-first mindset within organizations.
Since June 2021, Dewanjee has been serving as the Assistant Vice President of Data Science at HSBC Global Analytics Centre in Bangalore. In this role, he spearheaded the development of an XGBoost-based propensity model designed to identify emerging companies by analyzing factors such as industry, growth trajectories, founder profiles, and investor activities. This initiative facilitated early-stage banking relationships, resulting in a substantial $20 million in first-year incremental revenue. Additionally, he led the creation of a sophisticated look-alike clustering model utilizing the FAISS algorithm and semantic search mechanisms. By leveraging filmographies, financial data, and risk information from external datasets like Dun & Bradstreet, this model effectively identified new-to-bank companies with similarities to existing clients, generating an additional $5 million in annual revenue across 12 ASP markets.
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Before his tenure at HSBC, Dewanjee held the position of Senior Business Analyst at Amazon from December 2020 to May 2021. During this period, he assessed the impact of the COVID-19 pandemic on customer conversion rates and devised corrective measures across various facets, including the selection funnel, marketing strategies, inventory management, and delivery promises. He also conducted in-depth analyses of shopper behavior and brand profitability, aiding business owners in identifying key brands for the “Brand Accelerator Program.”
From November 2019 to December 2020, Dewanjee served as Assistant Manager of Operations Excellence at Noon. He led the design and development of a “Fulfillment Governance Framework” to monitor performance KPIs and focus on key improvement areas. This initiative resulted in a 10% improvement in perfect shipping and in-bounding adherence, as well as a 17% reduction in month-over-month inventory loss. Collaborating with the data engineering team, he also developed an analytics reporting layer that provided crucial insights and dashboards to support management decisions, process improvements, and re-engineering efforts for Noon’s grocery service launch. These efforts helped the fulfillment team maintain a 98% shipping adherence rate and less than 1% out-of-stock instances.
Earlier in his career, Dewanjee worked as an Assistant Manager of Business Consulting at HSBC Global Analytics Centre from November 2016 to October 2019. In this role, he provided decision support for the digital trade transformation project of documentary credit commercial checks operations. His contributions included translating business rules into technical frameworks, designing solutions, assessing service outage impacts, monitoring accuracy, and planning global rollouts.
Dewanjee’s professional journey began as a Business Analyst at EXL Decision Analytics from August 2014 to September 2015, where he performed delivery receipt audit analyses for accessory services to identify revenue leakages and conducted descriptive analyses to inform regular status reporting. He then transitioned to Jabong.com as a Business Analyst in Operations Intelligence from September 2015 to October 2016, where he developed a fulfillment cost estimation and allocation model to provide granular visibility of costs across the supply chain, supporting key strategic decisions.
In terms of education, Dewanjee earned his Bachelor of Engineering in Aerospace Engineering from the Indian Institute of Engineering Science and Technology (IIEST), Shibpur, graduating in April 2014 with a commendable CGPA of 8.1 on a 10-point scale.
Throughout his career, Dewanjee has developed a robust skill set that includes proficiency in technical tools such as Python, SAS, SQL, Tableau, GitHub, PyTorch, Langchain, MLFlow, GCP, Docker, and Airflow. His expertise in modeling techniques encompasses logistic regression, decision trees, random forests, gradient-boosted decision trees (XGBoost, LightGBM), neural networks, large language models, and transformers. His analytical capabilities span data wrangling, feature engineering, data visualization, data storytelling, and statistical analysis. Additionally, he possesses industry knowledge in global trade products, global payment solutions, B2B banking sales development, e-commerce operations, category management, and fraud management. His soft skills include team management, project management, stakeholder management, and project documentation and review.
