SUMMARY
Site Reliability Engineer with 6 years of experience in the tech industry, actively transitioning into a Data Analytics & Machine Learning role. Demonstrated capability in applying analytics and product-focused methodologies over the past 1-2 years through hands-on projects and internal implementations. Proven ability to leverage SQL, Python, and statistical modeling to drive business insights, optimize workflows, and support strategic decision-making. Adept in anomaly detection using statistical methods, regression, clustering, and translating business challenges into data-driven solutions using visualization tools. Also made hands dirty on projects related to LLM integration building
Mail : shebeebshe@gmail.com
Mobile : 7094185632/9489281032
MemoVita : The Full Fledged Memory Journaling App
While Mismatched app inspired from the Hindi series Mismatched and my small love story, I thought why not continue building it into full fledged memory journalling app not just for one person but to jounal about many loved ones in my life and yours too ….
Mismatched: The Memory App
Have you watched Mismatched, a hindi series? Can you believe a series and missing one had made me create this wonderful APP. Check this blog to know more on that …
Machine Learning
Insurance Premium Prediction: Segmented Modeling and Streamlit Deployment
MACHINE LEARNIG
Credit Risk Modeling: Predicting Loan Defaults with Machine Learning
MACHINE LEARNIG
Predicting Consumer Price Preferences – My Virtual Internship Project at Atliq Technologies
Data Analytics
Credit Card Launch Analytics: Journey with Banking Client
Data Analytics
AtliQ Grands Hospitality : Data Analysis
LLM BASED PROJECTS
NEWS CONTENT Summarizer bot : Building My first RAG based Chatbot
LLM BASED PROJECTS
NEWS CONTENT Summarizer bot : Building My first RAG based Chatbot
EXPERIENCE & SKILLS
1. Zoho Corp : May 2019 – Present
Site Reliability Engineer (SRE) | ML Engineer Transition
As an SRE, ensuring 100% uptime was the core responsibility. To enhance system reliability, designed and deployed an ML-driven Anomaly Detection System to monitor request response times and preemptively detect performance anomalies before critical failures.
- Designed and deployed an ML-based Anomaly Detection System to monitor response times and improve system reliability.
- Built a predictive model using XGBoost for time-series forecasting of web request trends.
- Applied Z-score and statistical techniques to detect anomalies and reduce incident response time by 50%.
- Collaborated with cross-functional teams to integrate AI-driven monitoring workflows into production systems.
- Identified workflow improvements and implemented scalable performance monitoring strategies.
- Participated in requirement gathering and solution design discussions with tech and business teams.
2. Atliq Technologies : 1 month virtual Internship
Data Science & Machine Learning Intern (Virtual)
Applied Data Science & Machine Learning techniques in a real-world business environment within the Food & Beverage industry.
- Applied ML and data analytics in real-world F&B business scenarios.
- Performed data cleaning, preprocessing, and feature engineering to boost model accuracy.
- Deployed predictive models and contributed to business-specific requirements gathering.
- Collaborated with clients to deliver scalable ML solutions.
Programming & Tools:
SQL, Python, C, C++, Java
Data Analysis & Visualization:
Pandas, NumPy, Seaborn, Matplotlib, Excel, Power BI, Tableau (Basic),
Data Science Concepts:
EDA, Feature Engineering, Data Preprocessing, Data Cleaning, Hyperparameter Tuning,
Statistical & ML Methods:
Hypothesis Testing, A/B Testing, Regression (Linear, Logistic), Clustering (K-Means), Z-score, Statistical Inference, Probability
Machine Learning & AI:
XGBoost, Random Forest, Classification, Neural Networks (Basics), Deep Learning (Basics), PyTorch, NLP, LangChain, LLM, RAG
Other:
Data Storytelling, Requirements Gathering, Technical Documentation, Business Insight Communication
Cloud & DevOps:
Streamlit, Git, Performance Monitoring
