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Lead Data Scientist with 7+ years in MIS, Dashboard Development & Machine Learning
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M.Sc. Statistics professional with 7+ years of experience of working into MIS creation, Dashboard Development, Data Reporting, Data Automation, Data Analytics and Data Science. Experienced into Data visualization, Dashboard Development in Power BI and automation by using tools like SQL, Power BI, Python, Alteryx and MS-Excel. DATA SCIENCE Certification holder having working experience in skills like Statistical Analysis, Linear Regression, Logistic Regression, Statistics, Random Forest, XGBoost etc.
University of Mumbai
M.Sc.- STATISTICS · STATISTICS
August 1, 2015 – June 30, 2017
G.N. Khalsa College
B.Sc.- STATISTICS · STATISTICS
August 1, 2011 – June 30, 2014
R.M. Bhatt Jr. College
HSC
June 1, 2009 – May 31, 2011
M.C. High School
SSC
June 1, 2007 – May 31, 2009
QUANTIQUE METADATA PVT. LTD.
AIML Data Scientist
December 19, 2024 – July 11, 2025
India
EMPOWER FINANCIAL SERVICES PVT. LTD.
Sr. Analyst
March 11, 2024 – December 18, 2024
India
AXIS SECURITIES LTD.
Deputy Manager
September 25, 2023 – March 7, 2024
India
SBICAP SECURITIES LTD.
Sr. Executive
February 22, 2021 – September 18, 2023
India
Hinduja Global Solutions Pvt. Ltd.
Data Analyst- Analytics & MI
July 4, 2019 – February 19, 2021
India
SYSTECH TECHNOCRAFT SERVICES PVT. LTD.
Statistical Consultant
December 4, 2017 – December 10, 2018
India
CAREER SELECTION AND JOB SATISFACTION
June 1, 2026 – Present
OBJECTIVES: To study the factors which influence on Career Selection among students also to analyze the job preferences among youth and to determine push and pull factors for job satisfaction among working people. CONCLUSION: Gender, Age, Better Career Options and Reservation System were found significant variables on career selection. The statistical techniques used were Logistic Regression, Factor Analysis, Pareto Analysis, Chi-Square Association testing and other techniques using different statistical tools.
ATTRITION EFFECT ON IBM HR DATA (Churn Analysis)
June 1, 2026 – Present
OBJECTIVE: Find out most significant factors of employees churn and suggest some necessary steps to retain those employees IBM HR Team. The techniques used is Logistic Regression to find out the factors of employees churn and feature engineering to increase the accuracy of the model and to retain the employees by focusing on those parameters.
CREATED A SQL RULE BASED SYSTEM THAT GIVES CLIENTS NOT TRADED IN SPECIFIED DURATION.
June 1, 2026 – Present
OBJECTIVE: Identify the customers who are potential for calling as they haven't traded and likely to trade once called. The SQL and Excel tools used to find out specific clients from SQL database and send the clients data to different dealers for calling purpose.
IDENTIFYING POTENTIAL CUSTOMERS FOR TRADING FROM DORMANT CLIENTS
June 1, 2026 – Present
OBJECTIVE: Identify the customers who are potential for trading after stopped trading in last 11 Months. Main objective to increase the daily trading count and brokerage earned from potential customers. The techniques used is Correlation matrix, Up sampling and Down sampling, Random forest, XG Boost, Logistic Regression at first and then based on increased accuracy of the model and other parameters RF is selected as final model for Prediction of potential customers.
PRODUCT DASHBOARD BY USING POWER BI
June 1, 2026 – Present
DASHBOARD: Created a dashboard that provides Daily, Monthly and since inception data along with analysis on the data. The dashboard also provides downloadable files by using multiple slicers. Security RLS added for data privacy and given access to the related stake holders.
IDENTIFYING POTENTIAL FRAUDS FOR MOTOR INSURANCE CLAIMS.
June 1, 2026 – Present
OBJECTIVE: Identify the potential fraud claims made for motor insurance claims. The techniques used is Motor insurance data and business logics, Preprocessing and sampling, Random forest final model for Prediction of potential frauds with 87% accuracy and recall of 75% that detects potential frauds.
Certificate course of DATA SCIENCE using R, Python and SAS
Unknown
June 1, 2026 – Present
Certificate course of DATA ANALYTICS using SPSS and SQL
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate has worked across various industries including finance (securities, wealth management), insurance, and consulting, demonstrating adaptability. The projects showcase a breadth of applications for data science, from academic research to professional problem-solving (e.g., customer churn, fraud detection, sales optimization). The experience in training junior analysts aligns with a collaborative and knowledge-sharing culture. The target role of 'Lead Data Scientist' aligns well with the candidate's experience in leading teams and developing complex models, suggesting a good cultural fit for a role requiring both technical depth and leadership.
Soft Skills & Operational Fit
The candidate's resume indicates experience in team handling and training junior analysts, suggesting leadership and mentoring capabilities. Project descriptions highlight problem-solving for business objectives (e.g., identifying potential customers, fraud detection), indicating a results-oriented approach. The focus on automation of reports and dashboards suggests an operational efficiency mindset. However, without specific psychometric or English test scores, a deeper assessment of communication clarity, work attitude, stress handling, and team collaboration is limited.