Machine Learning Data Analyst

ANILKUMAR NIMMA

Jersey City, New Jersey, ***** • 551-***-**** • ****************@*****.*** • LinkedIn SKILLS

Programming Languages: Python (pandas, NumPy, matplotlib, scikit-learn), SQL, R Data Analysis: Tableau, Power BI, Excel (Power Query), A/B Testing, Cohort Analysis, Regression Modeling Statistical and Machine Learning Techniques: C5.0 Decision Tree, Hypothesis Testing, Segmentation Analysis

(Clustering), Classification Reports, Confusion Matrix, Time-series Forecasting, Tools and Platforms: Google Analytics, CRM Systems PROFESSIONAL EXPERIENCE

Data Analyst (Intern) 2021 - 2022

Uncovered actionable insights by performing exploratory data analysis (Python), driving measurable business improvements.

Delivered executive dashboards using Tableau and Power BI, empowering real-time monitoring of business-critical KPIs.

Leveraged advanced Excel, including Power Query, to generate automated reports for timely strategic decision-making.

Executed A/B and hypothesis testing to measure the impact of product features and marketing initiatives across all segments.

Partnered with cross-functional teams to define and track key business metrics, aligning analytics with organizational goals.

Wrote and optimized complex SQL queries to perform ad hoc business analysis, answering high-priority executive requests.

Conducted statistical analysis and regression modeling to evaluate sales trends, highlighting opportunities to boost revenue.

Analyzed Google Analytics and CRM data, uncovering key drivers of engagement and recommending strategies to teams.

Identified root causes of customer churn with cohort analysis, supporting churn reduction with targeted recommendations.

Produced weekly business reports highlighting performance trends, anomalies, and actionable findings for senior review.

Collaborated with PMs to assess feature adoption, enabling prioritization of product roadmap based on analytical findings.

Validated findings by ensuring accuracy and consistency through data audits and integrity checks on all analytical work.

Supported marketing teams with segmentation analysis, identifying high-value segments for campaign development. APPRENTICESHIP

Vegetation Classification Using Machine Learning 2021 - 2021

Leveraged C5.0 decision tree to classify multiclass vegetation data, extracting patterns to improve ecological understanding.

Utilized cost-sensitive analysis to address class imbalance, ensuring reliable insight generation from environmental datasets.

Interpreted outputs via confusion matrix and classification reports to inform decisions on vegetation management strategies. EDUCATION

Rivier University, New Hampshire Jan 2023 - Dec 2024 Master's in Computer and Information Science

Gitam University June 2017 - June 2021

Bachelor's in Computer Science Engineering

CERTIFICATIONS

Python Data Structures

Machine Learning Algorithms

Cloud Computing

Python & Django full stack web development

Contact this candidate