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Data Science with 5+ years in Machine Learning & NLP
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Experienced Data Scientist Intern with a background in statistical analysis and process management. Skilled in building predictive and decision models using machine learning algorithms, analyzing large datasets for data insights, and deploying ML/NLP solutions. Proficient in Python, Machine Learning, Natural Language Processing, Deep Learning, SQL, Tableau, Power BI, and SAS, with a total experience of 5.3 years.
Pune University
B.sc · Statistics
August 1, 2012 – June 30, 2016
Infosys BPM Ltd
Senior Process Executive
August 1, 2024 – Present
Pune, Maharashtra, India
Ai Variant
Data Scientist Intern
November 1, 2022 – May 1, 2023
Pune, Maharashtra, India
Tech Mahindra
Customer Support Associate
October 1, 2020 – October 1, 2022
India
CYTEL Statistical Software Services Pvt. Ltd
Statistical Software Services
August 1, 2016 – April 1, 2017
Pune, Maharashtra, India
Resume Classification
June 1, 2026 – Present
Company wanted to improve their talent acquisition process by automating the resume categorization process using NLP approaches. Built an accurate model using Python libraries including NLTK, SpaCy, and scikit-learn to categorize resumes and reduced the review time for each resume from 5 minutes to 6-7 seconds, improving the effectiveness and shortening the recruiting process.
SAS Project
June 1, 2026 – Present
CRF Annotation, ADVS Data Creation, Shift Table, Quality Control of DM and AE report, Quality Control of SDTM data sets (Demographics and Disposition). Strong knowledge involving all phases (I-IV) of clinical trials. Understanding of SDTM and ADaM. Knowledge about procedures like PROC MEANS, PROC CONTENTS, PROC PRINT, PROC FREQ, PROC REPORTS, PROC FORMATS, PROC TRANSPOSE. Knowledge about functions like SCAN, SUBSTR, SUM, ROUND, CATX, TRIM, FIND, PUT, INPUT and DATE functions. Knowledge about SAS Access files like PROC IMPORT and EXPORT. Knowledge about SAS Options like KEEP, DROP and RENAME. Create reports in the form of listing, HTML, RTF and PDF formats using SAS ODS.
Stock Market Analysis and Prediction
June 1, 2026 – Present
The project involved evaluating three significant stocks, Reliance, Adani Green Energy, and Adani Transmission, to provide useful insights to potential investors. It required meticulous data collecting, cleaning, and analysis to extract patterns and trends from the dynamic stock market data. Python modules like Pandas and Beautiful Soup were used for data cleaning and web scraping, and statistical techniques such as moving averages, correlation analysis, and trend analysis were employed to find patterns and trends in the data. The project's findings provided specific investment advice with a model accuracy of 98%, and an interactive projected model using Streamlit enhanced the user experience.
UPS Logistic Process
June 1, 2026 – Present
Customer support associate. US base process. Invoice Corrections. Data correction work. Familiar with all work-related process management.
Data Analyst
ExcelR Solutions
June 1, 2026 – Present
Data Science
ExcelR Solutions
June 1, 2026 – Present
SAS Global Certified
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from NLP-based resume classification to stock market prediction and clinical trial data analysis (SAS), indicates a broad interest in applying data science across different domains. The experience as a Data Scientist Intern at Ai Variant aligns well with a data science target role. However, the current role as a Senior Process Executive at Infosys BPM Ltd, starting August 2024, is a significant deviation from a data science trajectory, which might raise questions about long-term commitment to data science. The certifications in Data Analyst and Data Science from ExcelR Solutions, along with SAS Global Certified, show a proactive approach to skill development. The blend of academic background in Statistics and practical project experience suggests a good foundation for analytical roles.
Soft Skills & Operational Fit
The candidate's resume highlights experience in customer support and process management, suggesting an ability to handle operational tasks and interact with stakeholders. However, specific soft skills like problem-solving, teamwork, or leadership are not explicitly detailed. The transition from customer support roles to data science indicates adaptability and a drive for career change.