Open to opportunities
BS
Years Experience
4+
▲ 3 companies
Engagement Growth
12%
▲ FloSports revenue forecasting
Ad hoc Request Drop
40%
▲ Mode governed dashboards
QA Turnaround Gain
27%
▲ Deloitte validation scripts
Impact Timeline — Efficiency Gains
% improvement delivered per role over time
Trending up
Analytics turnaround
Decision speed
Pipeline accuracy
Tech Stack Composition
Skills by domain area
6 domains
Data Eng
ML/AI
Analytics
Cloud
Programming
Data Science
Quantified Wins by Company
% improvements delivered across roles
3 roles
Core Competency Radar
Proficiency by area
Career Journey
From ECE foundation to Data Science Analyst
5 stages
B.E. Electronics Osmania Univ. 2017 to 2021 Deloitte USI DS Specialist 2021 to 2023 M.S. EE at USC ML and Deep Learning 2023 to 2025 Radical X AI Engineer Intern May to Aug 2024 FloSports Analytics Engineer Oct 2025 to Present ● CURRENT
Efficiency Gains Across All Roles
% improvement across key metrics
Cumulative Impact Score
Contribution growth by quarter
12% engagement lift
Role Details
Full experience breakdown
Oct 2025
to Present

● CURRENT
FloSports — Austin, TX
Data Analytics Engineer
dbt Snowflake Apache Airflow Mode Bayesian A/B
Architected dbt models on Snowflake, reducing analytics delivery time by 20% and supporting revenue forecasting that drove 12% growth
Deployed Apache Airflow pipelines to automate customer survey and A/B experimentation data ingestion, reducing manual intervention
Built governed Mode dashboards cutting ad hoc requests by 40% and enabling self serve analytics
Implemented Bayesian A/B testing for pricing and layout experiments, reducing decision time by 25%
Designed schema mappings and business rules enabling reusable data models and 99%+ data accuracy
May 2024
to Aug 2024
Radical X — New York, NY
Artificial Intelligence Engineer Intern
Vertex AI LangChain Streamlit GCP Docker
Built GenAI powered grading pipelines using Vertex AI, LangChain, and Streamlit achieving 89.6% accuracy in production
Optimized and Dockerized ML services on GCP reducing inference latency by 20% with privacy aware deployment
Collaborated with Product and Engineering across a full release cycle to define ML architectures and integrate model outputs
Sep 2021
to Jul 2023
Deloitte USI Consulting — Hyderabad, India
Analyst — Data Science Specialist
GCP Apache Airflow Teradata ETL MLOps Flask 2x Awards
Designed and deployed ETL pipelines on GCP orchestrated via Apache Airflow eliminating manual bottlenecks across client accounts
Built automated validation scripts on Teradata reducing QA turnaround by 27% and resolving cross system inconsistencies
Deployed MLOps pipelines supporting real time inference for 1000+ users across enterprise workflows
Ran A/B testing and causal analysis improving targeting precision and boosting engagement across 3 business units
Integrated Flask APIs with dashboards enabling 30% faster business decisions — earned 2 Deloitte Performance Awards
Domain Strength
Relative proficiency by discipline
Tool Usage — Frequency vs Depth
Bubble size = impact delivered
Skill Proficiency Index
Detailed breakdown with proficiency bars
SkillCategoryProficiencyLevel
SQL and dbtData Engineering
Expert
SnowflakeData Engineering
Expert
Apache AirflowData Engineering
Expert
PythonProgramming
Expert
TeradataData Engineering
Advanced
Power BI and ModeVisualization
Expert
Bayesian A/B TestingData Science
Expert
TensorFlow and PyTorchML and AI
Advanced
GCP and BigQueryCloud
Advanced
MLflow and MLOpsML and AI
Advanced
Apache SparkData Engineering
Proficient
Docker and KubernetesDevOps
Proficient
LangChain and Vertex AIML and AI
Proficient
NOV 2024 to DEC 2024
Real Time Twitter Sentiment Analysis
Built a real time sentiment pipeline using Logistic Regression and BERT processing 10K+ tweets per hour. Cleaned and engineered text features using NLTK and spaCy. Deployed a live Streamlit dashboard with Plotly for trend visualization.
82% Accuracy 10K+ tweets/hr BERT and NLTK
SEP 2024 to OCT 2024
Customer Churn Prediction Pipeline
Designed a churn prediction system using Logistic Regression and XGBoost. Engineered RFM features and tenure based segmentation to detect early churn signals. Achieved 84% accuracy and 0.88 AUC reducing customer loss by 13%.
84% Accuracy 0.88 AUC 13% Churn Reduction
Project Performance Metrics
Key results across both projects
Sentiment Pipeline
Churn Predictor
Contact and Links
bhavyamallineni@gmail.com
Email
(949) 547-0409
Phone
📍
Austin, Texas
Location
in
@bhavya-samhitha-mallineni
LinkedIn
@BhavyaSamhithaMallineni
GitHub
Education
2023 to 2025
University of Southern California
M.S. Electrical Engineering — Los Angeles, CA
ML, Deep Learning, Mathematical Optimization, Digital Image Processing
2017 to 2021
Osmania University
B.E. Electronics and Communication — Hyderabad, India
Signal Processing, Embedded Systems, Communication Theory
About Me

Data Science Analyst with 4+ years of experience building scalable ETL/ELT pipelines, ML models, and data architecture on GCP, Snowflake, and Teradata. Expert in Python, SQL, and Apache Airflow. I specialize in transforming petabyte scale datasets into actionable business insights through statistical analysis, A/B testing, and cross functional stakeholder collaboration with global teams.

Analytics Engineering Experimentation ML Systems Data Products AI Driven Decisions Storytelling with Data