Jeeve Singh

Reliance is India's largest private-sector company, with a gross revenue of £103bn in 2025. Its operations span O2C, digital services, retail, media, and renewables.

• Following FID on a new energy Giga Plant, Reliance New Energy required an overhaul of its existing statement models and DCF analyses to cut expenditure toward a group target of ≥25% energy-cost reduction, without negative effect on operations or consumer satisfaction.
• Eliminated 5 of 26 potential methods to complete the task by evaluating build-phase applicability, domain fit versus retained tools, and structural necessity under captive demand. Discarded methods relating to working-capital, portfolio-optimisation, and concession-revenue as inapplicable or redundant to a greenfield integrated build.
• Assessed the best method to deliver the 21 screened models, and settled on embedding them into three-statement and DCF models in Excel and Anaplan. Structured the deliverable around five categories: capital allocation, cost of capital, scale economics, cost-structure efficiency, and input-cost hedging.
• Equipped the finance team to rank new energy capital projects by NPV against WACC. Isolated controllable cost reductions from those that would diminish operations or product quality.

Jio is a subsidiary of Reliance Industries Limited, and serves as the digital services and telecom arm. JioCloud is a personal cloud-storage platform, letting subscribers store, back up, and access media and files across their devices.

• Ahead of JioCloud’s Diwali promotion, we were tasked with sizing the minimum free-storage allowance and smallest tier discount that would minimise churn, with specific instructions to ignore cost. Prior sale events could not be used as a comparative to estimate the non-linear, competitor-dependent relationship between offer size and churn.
• Identified 23 potential methods, before grouping them to eliminate those unsuitable for our churn-only, non-linear use-case. Eliminated 8 methods that related to linear-correlation, revenue-keyed demand, and portfolio-optimisation as inapplicable to our one-off, competitor-dependent estimation problem.
• Deliberated on the most efficient presentation method. Settled on embedding the 15 retained models into a single Excel workbook for decision-makers, structured around four categories: demand and competitor modelling, response estimation, uncertainty modelling, and optimisation.
• Equipped decision-makers to set the Diwali offer with quantified information on how each lever moved churn, where rival matching capped those effects, the confidence band around estimates, and the minimum offer that moved churn.

• xTend Prosthetics is a student-led charity that designs and 3D-prints prosthetic arms at rates 28× cheaper than the NHS. As a founding member, I led the financials of its first year before passing those responsibilities on.
• Independently built xTend's proprietary line-item-unit model, which is currently in practice.
• Designed xTend's bookkeeping system with best practices for a charity in mind.
• Modelled four funding scenarios from a 10-arm steady state to a 120-arm stretch case, quantifying NHS-equivalent cost avoided of £24k–£296k and identifying a single £25k Wolfson Foundation grant as sufficient to fund the full £3,378 capacity build plus 270+ subsequent arms. The Wolfson Foundation grant was successfuly secured.
• Codified a 14-funder UK grant pipeline (Wolfson, Bailey Thomas, Anton Jurgens, James Tutor et al.) with deadlines, owners, eligibility, and stage-based probability weighting. Yielded £93,500 in addressable funding for the first 12 months of 2025.
• Managed all financial operations culminating in the successful 2024 mission to deliver xTend's first prosthetic arm to a double amputee in Ksar el Kebir, Morocco. Completed successfuly within six months of xTend's founding.

• Decisionomics is a marketing decision intelligence platform that consolidates competitor tracking, campaign analytics, and social listening into a unified dashboard, enabling brands to make data-driven decisions in real time.
• Iterated on and built uplift and attribution models to measure the incremental effect of decisions on outcomes.
• Built a Prophet-based time-series forecasting model that uses the autoregressive integrated moving average (ARIMA) of consolidated data to project campaign KPI trajectories and anticipate competitor behaviour.
• Developed change-detection algorithms that enable real-time tracking of rival brand activity.