Open to DS/DE rolesAWS + SQLNLP/TransformersFull SDLC
Data Scientist • Software Engineer • Cloud + NLP/LLMs
I specialize in bridging the gap between complex data science and scalable software engineering. With 4+ years of experience across the full SDLC, I design robust data pipelines, architect cloud-native backends, and build intuitive front-end interfaces. My focus is on transforming raw data into high-performance enterprise tools whether that's fine-tuning LLMs for automation or optimizing real-time trading systems for 99.9% reliability.
DS/DE
Data pipelines, analytics, and ML across enterprise environments.
Cloud + SQL
AWS (EC2, S3, Glue, Lambda, SageMaker) + Oracle/SQL Server/Postgres.
NLP/LLMs
BERT fine-tuning, LangChain automation, and deployment workflows.
Experience
4+ yrs
FLHSMV + SNTIMNT.AI + Capgemini + Geneobits
Latency Reduced
70%
Real-time trading app improvements
Ops Efficiency
60%
Automation with Python & tooling
Uptime
99.9%
Tier 2/3 support & server reliability
Skills Snapshot
View allData Science & ML
scikit-learnTensorFlowPyTorchXGBoostTransformers/BERTNLPGenAILangChainTime Series (LSTM)EDA
Data Engineering
ETL/ELTSSISAirflowdbtFivetranData ModelingStored ProceduresSparkKafkaDatabricks
Cloud
AWS EC2S3RDSGlueLambdaSageMakerAmplifyRoute 53Azure ADFAzure Synapse
Recent Experience
View allApplication System Programmer III
Florida Highway Safety and Motor Vehicles (FLHSMV) • Florida, USA
Jul 2025 – Dec 2025
- • Designed and maintained enterprise applications using C#, ASP.NET MVC, and SQL to support mission‑critical operations with reliable performance and scalability.
- • Optimized workflows across Oracle Fusion, EBS, and PeopleSoft by building SQL/PL‑SQL reports, automating data processes, and integrating HR/payroll/financial systems.
- • Managed end‑to‑end SDLC (requirements → design → build → test → deploy → support) across Dev/QA/UAT/Prod environments.
C#ASP.NET MVCSQL ServerOraclePL/SQLSSMS
Team Lead
SNTIMNT.AI • Florida, USA
Jan 2025 – Apr 2025
- • Led a team of 5 to deliver a real‑time crypto trading app in Python, combining sentiment analysis + REST APIs for live automation.
- • Reduced data latency by ~70% through execution optimizations and tighter pipeline orchestration.
- • Fine‑tuned BERT on AWS EC2 and deployed via SageMaker; reduced model deployment time from ~8 hours to ~2 hours.
PythonREST APIsBERTAWS EC2SageMakerAmplify
Featured Projects
View allDynamic Airlift (NYC Air Quality Pipeline)
Automated pipeline + dashboard for real-time air quality monitoring and trend analysis.
AirflowETLDashboardsStatisticsAPIs
Stock Price Prediction (Time Series Forecasting)
LSTM-based forecasting pipeline with feature engineering and evaluation.
LSTMTime SeriesFeature EngineeringForecasting
Chronic Disease Prediction
ML models + Tableau visuals to identify high-risk demographics and improve interpretability.
GridSearchCVClassificationTableauModel Tuning