Headline

Data Analyst | Business Analyst | Fintech/BFSI/SaaS | SQL, Python, Superset, n8n | I automate the reporting so teams can act on churn, adoption & revenue faster

About

Data Analyst and Business Analyst with 3 years building the analytics infrastructure behind revenue and retention decisions in fintech and BFSI. I own product health analytics end-to-end at Synaptic — churn, engagement, and adoption tracking that's driven an 18% lift in DAU/MAU and 20% better retention coverage — and I partner directly with Product, Growth, and Customer Success stakeholders to turn that data into action. Before this, at Paisabazaar, I built automated Python and SQL pipelines across Business Loans, Credit Cards, and Personal Loans that cut the sales cycle by 20% and lifted lead conversions by 15%, working cross-functionally with sales and external stakeholders to redesign how coverage and conversion were tracked. What I actually do well: find the signal in messy CRM and product data, then automate the reporting around it so teams stop waiting on manual pulls and start acting on churn risk and upsell opportunity in near real time. Python and n8n automation alone cut manual reporting effort by 70% on my current team. Background: MCA + BCA in IT, plus a machine learning research stint at IIT Delhi predicting driver stress from physiological data (Maruti Suzuki dataset) Tools: SQL, Python, Apache Superset, Excel, n8n Open to: Data Analyst, Business Analyst, and Product Analyst roles in fintech, BFSI, Ecommerce and SaaS.

Location

Delhi

AI stack

claude code

claude

n8n

notion

ChatGPT

Work experience

Data Analyst at Synaptic, Jan 2025 - Present · 1 yr 9 mos, • Own end-to-end customer health analytics — engagement, adoption, and churn-risk KPIs — partnering with Customer Success and Product stakeholders on early risk identification; drove a 20% improvement in retention coverage and expansion pipeline visibility • Built automated reporting pipelines (SQL,Python, n8n, scheduled jobs) for Customer Success workflows, cutting manual effort by 70% and reporting turnaround time, enabling faster action on churn risk and upsell opportunities • Built and analyzed SQL-driven dashboards tracking MAU, DAU, and feature-level engagement; ran trend and drop-off analysis to identify low-adoption areas, driving targeted interventions that increased DAU/MAU by 18%, retention by 12%, and contributed to 8% revenue growth • Reduced manual customer engagement analysis effort by 60% by building AI powered analytics agent using n8n, OpenAI, Javascript and Google Sheets to automate engagement tracking across different customer accounts, generating actionable insights on open rates, content performance and churn risk signals

Business Analyst at Paisabazaar, Aug 2023 - Jan 2025 · 1 yr 6 mos, Gurugram, Haryana, India, • Extracted and cleaned CRM data across lending products to surface actionable insights for strategic decision-making; built advanced Excel models for ongoing reporting to leadership • Partnered with external SalesChat stakeholders to define and automate daily usage reporting for sales agents across multiple business lines, contributing to a 15% increase in lead conversions • Built automated SQL and Python pipelines tracking login, appointment, and disbursal coverage across Business Loans, Credit Cards, and Personal Loans — a 10% profitability increase through improved sales-funnel visibility • Supported a structural redesign of the Loans department into lead-qualification and closing teams; built automated pipelines and data-driven insights to optimize lead handoffs, improving conversion rates and cutting sales cycle by 20%

Business Intelligence trainee at IndiaMART InterMESH Limited, Jul 2023 - Aug 2023 · 2 mos, Noida, Uttar Pradesh, India, •Built and optimized a Freelancer Payout Datamart using SQL stored procedures and data modeling, working cross-functionally with engineering to integrate it into existing database systems; documented configurations and troubleshooting procedures to support ongoing maintenance

Machine Learning Reserach Intern at Indian Institute of Technology, Delhi, Feb 2023 - Jun 2023 · 5 mos, • Developed and fine-tuned multiple machine learning models using GSR values to accurately predict driver stress levels for a dataset provided by Maruti Suzuki, resulting in an overall accuracy improvement of 15%. • Conducted extensive research on industry standard preprocessing techniques and implemented them to clean and preprocess the raw data, resulting in a 30% reduction in false positives. • Collaborated with cross-functional teams to identify key features and parameters driving model performance, leading to the discovery of previously overlooked variables that improved model accuracy by 10%.

Education

Master of Computer Applications - MCA, Vivekananda Institute of Professional Studies

BCA, Information Technology, Vivekananda Institute of Professional Studies

Public links

github: https://github.com/anjali1227

leetcode: https://leetcode.com/anjali1227