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Aathira Suresh

Analytics @ PayPal | Fraud & Risk | Building toward Product

India

4+ years of work experience

PayPal
May 20251 yr 7 mosPresent

Bengaluru, Karnataka, India

Designed 2 reusable AI-agent workflows for automated fraud-rule backtesting and recommendation, cutting rule-evaluation turnaround by ~60% across 40+ merchant cases. Co-built a closed-loop automation platform (alert → ML-recommended rule → merchant-ready deck) as part of a self-serve console for merchant-facing teams, driving 5x faster ticket turnaround and 75% fewer inbound tickets. Led design of a real-time fraud spike-detection system to flag abnormal transaction volume, enabling proactive rule recommendations ~2–3 weeks faster than waiting for chargebacks to mature. Defined a cross-merchant fraud rule validation framework (precision ≥40%, recall ≥30%) and deployed it across 5+ merchants, rejecting $3.95M in fraudulent volume with up to 97% precision. Partnered with Sales to define churn-risk signals, then built automated FPA churn reporting that drove ~30–40% re-engagement of at-risk merchants.
PayPal
Sep 20249 mosMay 2025

Hyderabad, Telangana, India

Built self-serve Tableau dashboards for chargebacks, declines, and approvals by segment, cutting ad-hoc analysis requests by ~40%. Led platform work to externalize PayPal's Braintree risk scores as a standalone product surface, enabling risk-score access for 10+ external merchant integrations. Standardized risk-scoring and threshold configuration across 40+ merchant onboardings, with rules achieving up to 91% precision while capturing 38% of fraud.
Tekion Corp
Apr 20246 mosSep 2024

Bengaluru, Karnataka, India

Contributed by devising SQL queries to efficiently migrate data to Tekion from various source systems used by automotive dealers. Also developed automation queries in SQL to expedite validation processes and enhance overall efficiency. Conducted review sessions to gain a deep understanding of project requirements which often involved collaborating with cross-functional teams to address any development-related challenges.
Tekion Corp
May 20222 yrsApr 2024

Bengaluru, Karnataka, India

Primarily focused on developing models that could seamlessly integrate with Tekion's product which involved working with data sourced from the legacy DMS and building these models from scratch, aligning them with provided requirements right up to the production phase. Built Tableau dashboards to track key performance metrics for the recommendation system, enabling data-driven evaluation of feature effectiveness.
The Sparks Foundation
Feb 20222 mosMar 2022

Exploratory Data Analysis- Performed data mining on a Terrorism dataset and drove insights on the same Tableau- Created a Dashboard and a Storyboard showing the spread of Covid-19 across different countries and regions Unsupervised Learning- Built a K-Means Algorithm by identifying the optimal value of clusters using both elbow method and silhouette score

Aathira’s AI Stack

claude
claude
gemini
gemini
openai
openai

Education

BITSoM - BITS School of Management

Certificate Program, Product Management with Generative & Agentic AI

BITSoM - BITS School of Management

20262026
Great Lakes Institute of Management

Postgraduate Degree, Data Science and Engineering

Great Lakes Institute of Management

20211 yr2022

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Headline

Analytics @ PayPal | Fraud & Risk | Building toward Product

About

I turn transaction, fraud and platform data into product decisions. Over 4+ years across fintech (PayPal) and SaaS (Tekion), I've partnered with product, engineering and business teams to define the metrics and validation logic behind what ships. At PayPal, I work with the Fraud Protection product team, building a precision/recall validation framework that governs which reject rules go live across high-risk merchants, shipping a real-time fraud-spike detection capability, and turning churn/risk data into Sales plays that re-engaged 30–40% of at-risk merchants. At Tekion, I owned the data models behind the Dealer Management System, integrating 12+ legacy systems from requirements through production. I'm strongest where data meets product judgment: metric design, A/B testing, funnel/cohort/churn analysis, and translating messy data into a clear recommendation. Tools I live in: SQL (BigQuery, Presto, Athena), Python, Tableau. Alongside my analytics work, I'm expanding into product management with Generative & Agentic AI, bringing a data-first lens to how products are shaped and decided. Open to Product Analyst and Business Analyst roles. Reach me at aathirasuresh99@gmail.com.

Location

India

AI stack

claude

gemini

openai

Work experience

Data Scientist (Product Analytics) at PayPal, May 2025 - Present · 1 yr 7 mos, Bengaluru, Karnataka, India, Designed 2 reusable AI-agent workflows for automated fraud-rule backtesting and recommendation, cutting rule-evaluation turnaround by ~60% across 40+ merchant cases. Co-built a closed-loop automation platform (alert → ML-recommended rule → merchant-ready deck) as part of a self-serve console for merchant-facing teams, driving 5x faster ticket turnaround and 75% fewer inbound tickets. Led design of a real-time fraud spike-detection system to flag abnormal transaction volume, enabling proactive rule recommendations ~2–3 weeks faster than waiting for chargebacks to mature. Defined a cross-merchant fraud rule validation framework (precision ≥40%, recall ≥30%) and deployed it across 5+ merchants, rejecting $3.95M in fraudulent volume with up to 97% precision. Partnered with Sales to define churn-risk signals, then built automated FPA churn reporting that drove ~30–40% re-engagement of at-risk merchants.

Data Analyst II at PayPal, Sep 2024 - May 2025 · 9 mos, Hyderabad, Telangana, India, Built self-serve Tableau dashboards for chargebacks, declines, and approvals by segment, cutting ad-hoc analysis requests by ~40%. Led platform work to externalize PayPal's Braintree risk scores as a standalone product surface, enabling risk-score access for 10+ external merchant integrations. Standardized risk-scoring and threshold configuration across 40+ merchant onboardings, with rules achieving up to 91% precision while capturing 38% of fraud.

Data Analyst I at Tekion Corp, Apr 2024 - Sep 2024 · 6 mos, Bengaluru, Karnataka, India, Contributed by devising SQL queries to efficiently migrate data to Tekion from various source systems used by automotive dealers. Also developed automation queries in SQL to expedite validation processes and enhance overall efficiency. Conducted review sessions to gain a deep understanding of project requirements which often involved collaborating with cross-functional teams to address any development-related challenges.

Associate Data Analyst at Tekion Corp, May 2022 - Apr 2024 · 2 yrs, Bengaluru, Karnataka, India, Primarily focused on developing models that could seamlessly integrate with Tekion's product which involved working with data sourced from the legacy DMS and building these models from scratch, aligning them with provided requirements right up to the production phase. Built Tableau dashboards to track key performance metrics for the recommendation system, enabling data-driven evaluation of feature effectiveness.

Data Science and Business Analytics Intern at The Sparks Foundation, Feb 2022 - Mar 2022 · 2 mos, Exploratory Data Analysis- Performed data mining on a Terrorism dataset and drove insights on the same Tableau- Created a Dashboard and a Storyboard showing the spread of Covid-19 across different countries and regions Unsupervised Learning- Built a K-Means Algorithm by identifying the optimal value of clusters using both elbow method and silhouette score

Education

Certificate Program, Product Management with Generative & Agentic AI, BITSoM - BITS School of Management

Postgraduate Degree, Data Science and Engineering, Great Lakes Institute of Management