Sep 2023 – Aug 2025 · 1 yr 11 mos · London, England, United Kingdom · On-site

• Spearheading the AI strategy through development of a comprehensive cash flow forecasting model by processing 2 yrs data of payment behavior, risk profile of debt to predict future inflows, thus facilitating strategic budgeting.
• Streamlined cash collection process by developing AI-powered customer risk scores based on payment patterns, region, employee interactions, developed BI dashboards for proactive prioritization of high-risk customers/invoices; Successfully reduced company debt from $42M to $37M and decreased overdue invoices by 50% (from $8M to $4M).
• Developing an automated SaaS PnL model by incorporating M&A by SHL.

Jun 2023 – Aug 2023 · 2 mos · London, England, United Kingdom · On-site

Sep 2022 – Aug 2023 · 11 mos · London, England, United Kingdom · On-site

Dec 2020 – Aug 2022 · 1 yr 8 mos · Gurugram, Haryana, India

• Launch of SHL’s Go-To-Market strategy.
• Led the development of algorithms, definitions, and metrics for the new strategy.
• Analysed customer response, usability, and contract burn tracking logic to improve the methodology continuously.
• Unlocked cross-sell and upsell opportunities worth $5M across 600+ clients.
• Product Insights.
• Utilised machine learning to map dependencies between customers and usage, demographics, language, and devised KPIs to identify behavioral patterns, reduced customer churn and incomplete assessments by 23% QoQ
• Analysed and tracked the launch of SHL mobile app, recommendations helped increase app usage demand by 4% MoM.
• Improving internal efficiency.
• Led the development of analytical insights for platform development and production support teams, thereby improving task prioritization and personnel efficiency, leading to a decrease in turnaround time by 12%.

Sep 2019 – Dec 2019 · 3 mos · Remote

• Analysed and identified issues with the segmentation process of farmlands, based on soil quality and
• crops grown, and developed a robust methodology to enhance land allocation and utilize smart farming
• Monitored & trained candidates in the development of metrics and visualization software for the algorithm

Jul 2019 – Nov 2020 · 1 yr 4 mos · Gurgaon, India

• Analytics & Data Science:
• Managed a 2-member team to analyse metrics impacting quality of location data, and formulated the Data Supply Rationalization plan for onboarding, blacklisting and cost determination of location data providing partner apps. Data Expense decreased by 45%, which amounts to $1.4 Mn.
• Envisioned and created an AI-powered clustering algorithm, with Adjusted Rand Index (ARI) of 0.74 against Facebook API dataset, to identify 7 Mn employee-store pairs and cut down irrelevant ads, enabled savings of $3.5 Mn annually.
• Worked collaboratively with the Engineering team to develop a process that filters location signals having high speed and low horizontal accuracy, thereby improving data quality and audience building procedure and reducing server load by 11%.
• Product Enhancements:
• Led Product team to conduct requirement analysis, study user journey and interaction using Heap Analytics tool, manage roadmap, define milestones, and perform MoSCoW prioritisation of company’s Ad serving and Insights platforms, to recommend enhancements using agile framework. The process helped to improve user experience, ease of flow, category prioritization and reduce dropout rate on two major platforms – Ads Manager and Location Intelligence Platform, resulting in higher conversion of prospective clients by 8%.
• Acted as the point of contact and delivered process requirements and documentation for getting the Media Rating Council (MRC) accreditation for accurate location data.

Oct 2017 – Jul 2019 · 1 yr 9 mos · Gurgaon, India

• Analytics & Data Science:
• Devised a probabilistic methodology by utilizing statistical analysis and decision tree on geometrical features, to improve the QA process of Blueprints (virtual boxes drawn over maps for advertisement targeting), thereby achieving a 60% error-detection rate of manually created Blueprints.
• Investigated visitation patterns and guided the formulation of targeted ad campaigns for a leading fast-food chain in Germany. The analyses helped clicks per ad impression (CTR) to increase by 35%.
• Product Enhancements.
• Analysed data collection pattern of internally built SDK (widget created to collect location signals), to reduce collection frequency by 30%, thereby decreasing battery consumption in mobile phones. Regularly performed an analytical study of newly launched SDK versions on apps to detect probable flaws and recommend future modifications.

Aug 2016 – Oct 2017 · 1 yr 2 mos · Gurgaon, India

• Member of the Data Science – Product BI team.
• Was involved in hands-on strategic development, business intelligence, and the development of statistical methodologies.
• Developed an algorithm that classified product reviews using Bayes classifier, quantified customer
• experience polarity, sentiment comparison, and provided frequency-based product recommendations to users on the E-commerce website and app thus boosting user experience and increasing cross-sell by 10%.
• Developed a tool to suitably visualize the cause of the rise/fall of metrics diving to the most granular level. Used language R for database access and data manipulation. Incorporated Tableau for color-based visual perception of metrics above/below twice the standard deviation.
• Developed Customer Experience Dashboard for improved data perception. Currently the most popular dashboard for precisely solving buyer experience, product quality, pincode serviceability, inventory distribution, and supply chain issues.
• Coordinated with the Ads data science team, to develop logic for the assignment of sellers to business units based on their campaigns and burns. Incorporated and unified Ads metrics for better classification and performance measurement on monthly basis.
• Involved actively in the Brand Monetization project. Incorporated brand comparison under various categories including grains for Tier, Zone, Price range, and discount provided. Each comparison graph provides multidimensional insight into selected brands' performance.
• Have performed detailed analysis on sellers to gain insights about inventory storage days and seller behavior on the Snapdeal platform. Also analyzed the effect of gender variability on products bought.

May 2015 – Jul 2015 · 2 mos · Urbana-Champaign, Illinois Area

• Learnt Charm++, a message driven, object oriented, parallel programming language based on C++, developed at UIUC
• Modified Rubik mapping tool to provide tilt operation on application grid in cyclic and combinatorial order. Modified the Rubik mapping tool, initially built for IBM BlueGene P/Q supercomputers, for Blue Waters/ Cray machines
• Developed a program that discovers topology of torus processor grid using process id, node id and coordinates in the grid. Designed code could discover holes from the huge processor grid provided by cray supercomputer
• Appended code to provide a compact view of processor grid for better visualization and application of partitioning and permuting operations
• Tested the program results on supercomputer Blue Waters of NCSA (National Centre for Supercomputing Applications)

May 2014 – Jul 2014 · 2 mos · Melbourne, Australia

• Worked on the development of new energy dissipating devices and connections having better hysteretic properties or "flag shaped behaviour".
• Provided a comprehensive parametric study and determined the possible dimensions of the devices. Assisted in study of two types of dissipation devices: one which combines the buckling restrained fuse type dissipater with shape memory alloy rods and the other with sliding friction energy dissipator. Force-displacement relationship of the two devices was tested to be in compliance with the design basis earthquake.
• Gained knowledge about the usage and working principle of devices previously made such as hybrid system, sliding hinge joint, ring springs, blind bolted connections and buckling restrained braces.