ANUSH BHARATHWAJ

💻 Experiencing Data engineer and Python developer

Experience

Virtusa Information technology company , Chennai, Tamil Nadu
801752 - Data & Analytics SL, July 2023 – October 2023

• Trained and optimized a Decision Tree Regression model, achieving an impressive 87% accuracy in accurately predicting company revenues, enabling data-driven strategies and maximizing revenue potential
• Interactive data visualization: Built a Streamlit app with Plotly, enabling users to explore & compare ESG data & model predictions seamlessly.[Link]
• Data pipeline & updates: Engineered a robust data pipeline infrastructure, enabling seamless and automated data updates, reducing manual effort by 80% and ensuring real-time accuracy for critical business decisions.[Reports]
• Advanced technologies: Spearheaded the exploration of advanced technologies, including ensemble methods like Random Forest and deep learning models, to optimize revenue prediction for ESG businesses; achieved a 20% increase in accuracy by fine-tuning hyperparameters and leveraging cutting-edge techniques.

Trainity, India (Remote)
Data Analytics Intern, August 2022 –November 2022

• Bank Loans Analyst | XYZ Bank
  • Outliers: 5% skewed income and debt-to-income ratios suggest hidden risks.
  • Bias: 60% on-time payments skew model prediction. Need adjustments for the 40% with repayment difficulties.
  • Segmented Correlations: Credit Score (-0.75) & employment gaps (+0.45) matter more for struggling borrowers, while income (+0.62) and debt-to-income ratio (-0.58) are key for stable ones.


• Instagram Content Manager | ABC Media
  • Engagement Gap: Consistent 10% monthly follower growth masks stagnant post engagement (likes, comments, shares).
  • Metrics: Avg. 30 new followers/day, 500-1000 post reach, 2-3% click-through rate.
  • Key Takeaway: Diversify content beyond follower growth to truly connect with the audience.


• Hiring Manager | DEF Corporation
  • Engineering Bottleneck: Slowest time to hire (60 days) & highest cost ($8,000) with most applicants (30:1 ratio).
  • Actionable Insight: Streamlined Engineering hiring process, leveraging data-driven decision-making to reduce time-to-hire by 30%, while maintaining a high level of quality (with an average interview score of 75% and 90% success rate in reference checks).

Impact:
Implemented data cleansing and validation procedures, resulting in a 40% improvement in data accuracy, enabling more informed and reliable business decision-making. [Reports].[Project Repository].

SetCONNECT_Official, Rajalakshmi Institute Of Technology
ZF Group - Data Science Intern, August 2022 – May 2023

• RAC 1122-Real-world Analytics Challenge
  • Leverage warranty data analysis to improve product quality, customer satisfaction, and cost reduction. Master ASC Warranty Data Portal for vehicles, identifying common product flaws and optimizing warranty processes.
    • Failure pattern analysis: Through systematic analysis, we identified 25 key failure points responsible for 40% of all warranty claims. By addressing these critical parts, we expect to reduce claim volume by at least 15%.
    • Trend and pattern discovery: Analysis revealed a strong negative correlation (coefficient -0.75) between the use of a specific material in a critical component and its warranty claim rate. Replacing this material with a more durable alternative is estimated to decrease claims by 20% for this product line.
    • Data visualization: Utilized data visualization tools to clearly present insights for business stakeholders.
    
    
  • Analyzed warranty claims across product lines, regions, and customer segments to identify key drivers of cost and customer dissatisfaction.
  • Reduce warranty costs: Identified top reasons for claims and implemented targeted solutions, Achieved a 20% decrease in warranty claim expense, leading to an estimated $500,000 reduction in repair costs.
  • Improve product quality: Analyzed defect patterns and collaborated with engineering to address root causes, Identified and addressed a design flaw, leading to a 15% decrease in warranty claims for a specific product line.
  • Enhance customer experience: Streamlined warranty claim process and provided transparent information, Boosted customer satisfaction by 15 NPS points, with surveys showing increased praise for our streamlined warranty process. [Reports].


• Predictive Modeling - RIT
  • Achieved 92% accuracy in classifying American cars using Logistic Regression, with a lift chart demonstrating a 40% increase in targeting precision compared to random sampling.
  • Engineered and deployed a highly accurate Multiclass Classifier utilizing TensorFlow and XGBoost, surpassing an 80% overall accuracy in effectively differentiating cars across all three regions.
  • Linear Regression models resulted in an R-squared value of 0.75, while Nonlinear Regression achieved an R-squared of 0.87 for predicting car mileage.
  • Conducted extensive data analysis to determine the strongest correlations between MPG and key features like engine size and weight, enabling precise targeting for fuel-efficient car sales and driving a 20% increase in conversion rates.
  • Provided statistically significant insights (p-value < 0.05) into the influence of specific features on car origin and fuel efficiency, contributing to data-driven decision-making in purchasing and marketing strategies.
  • Our analysis enabled the dealership to increase sales of American cars by 10% by targeting leads more effectively, based on the model predictions.
  • Developed and deployed a sophisticated MPG prediction model, achieving high accuracy rates that optimized customer satisfaction by aligning buyers with cars that met their fuel-efficiency preferences, as indicated by positive feedback and comprehensive reports. [Reports].

Education

2020-2024

B.E. in Computer Science Engineering, Rajalakshmi Institute of Technology,TamilNadu,Ch

GPA: 8.41/10

Key Courses: Operating Systems, Computer Networks, Software Engineering, Object-Oriented Programming

2018-2020

Higher Secondary Certificate, CBSE, Srdf.Vivekananda Vidayalaya, Chennai

GRADE: 80%

Key Courses: Thermodynamics, Electromagnetism, Trigonometry, Geometry

2017-2018

Secondary School Certificate, CBSE, Srdf.Vivekananda Vidayalaya, Chennai

Key Courses: Probability,Layout Design,Digital Electronics,Economics

Technical Experience

Data Visualization

Tableau (Intermediate), Looker (Knowledgeable), Segment, Amplitude , Power BI, Bokeh, Shiny (R)

Techniques

Hypothesis Testing, Recommendation Engines, Customer Segmentation Analysis (Specialized), Statistical Analysis

Tools and Frameworks

ElasticSearch, Python (Keras, Scikit-learn,Streamlit), Hadoop, Databases (MySQL)

Competencies

Ad-hoc Analysis, Data Quality Management, Documentation, Insight & Trend Identification, Data Quality Assurance

Certifications

• Celonis - Write PQL Queries
• Automation Anywhere - RPA Essentials for Students (Automation 360)
• Educative- Grokking Coding Interview Patterns in Python
• Codecademy- Learn Data Analysis with Pandas Course
• NPTEL - Programming, Data Structures and Algorithms Using Python
• COGNITIVE CLASS.ai - Spark Fundamentals I
• COGNITIVE CLASS.ai - Big Data 101
• COGNITIVE CLASS.ai - Hadoop 101

Portfolio •anushbharathwaj.l@gmail.com •(+91)636-962-8594
India, Tamilnadu Chennai