Ankit Yadav
Ankit Yadav

Data Analyst

Actively looking · Member since 6 Oct 2026
Location
Delhi, India
Desired salary
Unspecified
Work preference
Remote Only / Internship
Experience level
Junior

About

Professional summary

I am a Data Analyst candidate with a B.Tech in Computer Science Engineering from Delhi Technological University. I specialize in turning complex customer, collection, and operational data into clear insights and actionable recommendations.

I have hands-on experience with SQL, Python, Power BI, Excel, Tableau, statistical analysis, and dashboard development. My work includes portfolio performance analysis, root-cause analysis, customer segmentation, KPI tracking, and risk monitoring.

During my internship at Godrej Properties, I analyzed North Zone customer and collection data across projects, helping improve decision-making efficiency and collection outcomes. I worked closely with senior business stakeholders to translate analytical findings into practical recommendations.

I have built predictive analytics projects using Python, Pandas, and Scikit-learn, including a customer churn risk model based on logistic regression. I am comfortable applying machine learning and statistical methods to identify risk drivers and support revenue-impact decisions.

I also developed a multilingual speech-to-Indian Sign Language translation solution as a DTU capstone project. This work involved rule-based processing, translation tools, OpenCV rendering, and converting multiple input formats into sign-language video output.

I am interested in data analytics, business intelligence, automation, and continuous improvement. I bring strong communication, stakeholder reporting, leadership, and mentoring experience alongside my technical skills.

Skills

19 capabilities

Tech stack & tools

Working toolkit

Data Stores

Development

Experience

Career history

Intern Godrej Properties Limited, North Zone

Built portfolio performance analysis for North Zone customer and collection data across all projects using SQL and Power BI, improving decision-making efficiency by 30%. Conducted trend and root-cause analysis of payment behavior and outstanding balances, supporting a 50% improvement in collection efficiency.

Developed customer segmentation and prioritization models for higher-risk segments, contributing to a 19% increase in targeted collections. Designed an interactive customer lifecycle dashboard for behavior and KPI monitoring, which was received by Head Office and entered beta testing.

Created a risk-monitoring framework covering weather, pollution, regulatory, and construction factors to support proactive decision-making. Worked directly with the North Zone Collection Head and Senior General Manager to turn analysis into business recommendations.

Education

Learning history

Delhi Technological University (DTU)

B.Tech, Computer Science Engineering

Coursework included Business Analytics, Statistics, Database Systems, Data Structures and Algorithms, and Operating Systems.

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