Himanshu Ojha
From Data to Dollars š” | ML Expert for Your Business Challenges
#DataScience #MachineLearning #AI
About Me
Professional Summary
Results-driven Risk Management Analyst & Data Scientist with 2+ years of experience in investment risk oversight, regulatory reporting, and quantitative analysis. Expertise in implementing ML models, risk exception management, and governance reporting.
Proficient in Python, SQL, PySpark, Power BI, and Scala, with a strong foundation in financial risk management. Adept at automating risk reporting, analyzing large-scale financial data, and ensuring regulatory compliance to optimize risk strategies and decision-making.
Technical Skills
Skill Proficiency
Risk Management
Languages & Tools
ML/AI
Big Data
Professional
Data Science & Analytics Skills
My expertise spans across data science and analytics, with specialized focus on financial risk management and regulatory compliance.
Data Visualization & Analytics
Specialized in creating interactive dashboards and statistical visualizations using Power BI, Tableau and custom JavaScript frameworks for financial risk analysis and regulatory compliance monitoring.
Data Analytics Process
My approach to data analytics follows a structured methodology from business objectives to deployment and monitoring, ensuring comprehensive risk assessment and regulatory compliance.
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This dashboard provides real-time insights into driver attrition factors, helping identify at-risk drivers and implement retention strategies.
Monitor investment risk metrics in real-time with automated alerts and compliance tracking for regulatory requirements.
Data Analytics Framework
My comprehensive approach to data analytics encompasses enterprise solutions, data collection, quality assessment, integration, and visualization to deliver actionable insights.
"Himanshu's risk management dashboards transformed our compliance monitoring process. The interactive visualizations and automated exception tracking provided unprecedented clarity into our regulatory requirements."
Featured Projects
Overview
Implemented innovative personalization algorithms for e-commerce platforms using open source ML frameworks.
Key Contributions
- Applied statistical models and computer science principles to analyze user-generated content
- Worked with product managers to design systems that improved user experience and supported decision making
- Utilized GPU-accelerated computing and Scala for processing large databases in real-time
Technologies
Performance Metrics
Work Experience
Netflix
October 2024 - November 2024
Freelance Lead Data Scientist - SaaS Product Analytics
Walmart
August 2024 - September 2024
Freelance Senior Business Analyst - Quantitative Research
Target
June 2024 - July 2024
Freelance SQL Data Analyst - Analytical Application Development
Ola
January 2024 - February 2024
Freelance Data Analyst - SaaS Product Optimization
š§āš» Freelance Lead Data Scientist - SaaS Product Analytics
Netflix | October 2024 - November 2024
š Remote / On-site as needed
Overview:
Engaged by Netflix to enhance their SaaS analytics infrastructure and recommendation engine performance through advanced ML techniques and large-scale data processing.
Key Contributions:
- Delivered GPU-accelerated ML solutions for recommendation systems, achieving +25% performance improvement.
- Processed and analyzed 600M+ daily user events to extract actionable UX insights.
- Built real-time data pipelines supporting agile product decision-making.
Tech Stack:
š Python, š¤ Scikit-learn, š„ PyTorch, šļø Airflow, š¾ SQL, š Tableau, š³ Docker, āļø AWS
š§āš» Freelance Senior Business Analyst - Quantitative Research
Walmart | August 2024 - September 2024
š Remote / On-site as needed
Overview:
Contracted to support quantitative research and real-time system monitoring for Walmart's e-commerce UX optimization and performance tracking.
Key Contributions:
- Conducted advanced statistical analysis to uncover user behavior patterns.
- Developed real-time monitoring tools, leading to a +10% ROI increase.
- Aligned data models with business objectives through close collaboration with stakeholders.
Tech Stack:
š Python, š¾ SQL, š Pandas, š§® NumPy, āļø Power BI, ā±ļø Kafka, š¦ Git
š§āš» Freelance SQL Data Analyst - Analytical Application Development
Target | June 2024 - July 2024
š Remote / On-site as needed
Overview:
Hired by Target to optimize backend SQL workflows and create scalable analytical dashboards for product and marketing analytics teams.
Key Contributions:
- Optimized high-volume SQL queries and databases, achieving +18% performance boost.
- Developed KPI dashboards to track business metrics in real-time.
- Designed scalable infrastructure to handle growing e-commerce data loads.
Tech Stack:
š¾ SQL, š Python, š Power BI, š Tableau, š§ DAX, š Excel VBA
š§āš» Freelance Data Analyst - SaaS Product Optimization
Ola | January 2024 - February 2024
š Remote / On-site as needed
Overview:
Collaborated with Ola's analytics team to optimize ride-hailing operations through machine learning models and marketplace monitoring systems.
Key Contributions:
- Built predictive models to balance supply and demand across regions.
- Designed real-time dashboards and alerting systems for marketplace analytics.
- Conducted behavioral data analysis to support feature rollout and UX improvements.
Tech Stack:
š Python, š¤ Scikit-learn, š¾ SQL, š Plotly, š Tableau, āļø GCP, š ļø Streamlit
Education & Certifications
Focus on Statistics, Computer Science, and Innovation in Data Science
Quantitative Engineering Focus with courses in Statistics and Computer Science
Course Curriculum
- Zee Recommender Systems100/100
- AdEase Time Series96.5/100
- Scaler: Clustering100/100
- OLA: Ensemble Learning92.0/100
- LoanTap: Logistic Regression100.0/100
- Jamboree Education: Linear Regression93.0/100
- Delhivery Feature Engineering100.0/100
- Yulu: Hypothesis Testing100.0/100
- Walmart: Confidence Interval & CLT98.0/100
- Aerofit: Descriptive Stats & Probability91.0/100
- Netflix: Data Exploration and Visualisation93.0/100
- Target: SQL80.0/80
Programming
Python, SQL, PySpark, R, Scala
Machine Learning
Supervised, Unsupervised, Deep Learning
Big Data
Spark, Hadoop, ETL Processes
Visualization
Power BI, Tableau, Data Studio
Data Science & Machine Learning Certification
Successfully completed the comprehensive Data Science program at Scaler Academy with a focus on Risk Management and Financial Analytics.
Data Science Blog
Insights, tutorials, and case studies on data science, machine learning, and risk analytics
Missing data is a common challenge in data science. If not handled properly, it can lead to biased results and inaccurate predictions. Learn about different imputation techniques, focusing on KNN Imputation.
The logistics and delivery industry is undergoing a digital transformation, with data science playing a crucial role in optimizing supply chains, reducing costs, and improving customer experience.
Employee retention is a major issue in ride-hailing companies. We developed a machine learning model that predicts whether a driver will leave the platform, enabling proactive retention strategies.
Ensemble learning enhances model accuracy by combining multiple weak learners. The two most popular methods are Bagging and Boosting. Learn the differences and when to use each approach.
Imbalanced datasets can lead to biased models. Learn effective strategies for dealing with imbalanced datasets in classification problems, from resampling techniques to algorithm modifications.
Neural Networks have revolutionized AI, but are they always the best choice? This guide helps you choose between neural networks and traditional machine learning algorithms for different types of problems.
Get In Touch
Rajasthan, India