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About

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Mohit Appari

Data Scientist
APD State of Florida
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I'm an AI/ML engineer with 3+ years of experience building machine learning, GenAI, forecasting, and data-intensive systems across research and production — neural networks, LLM-powered applications, and time series models that solve real problems in finance, government, and research. I currently work as a Data Scientist at the Agency for Persons with Disabilities (State of Florida), building spending and budget forecasts over millions of transactional records covering 60K+ clients and $200M+ in monthly spending. Before that I wrote production software at S&P Global, where I led the migration of legacy .NET document-processing workflows to a Python extraction platform handling 10,000+ documents a day, and researched equivariant neural networks for materials science at Florida State University. I like sitting at the intersection of deep learning, math, and finance, and I'm always chasing problems that are hard enough to be interesting.

I'm eager to contribute to AI engineering initiatives that bridge deep learning research with real-world impact.

Day to day, I work across the ML stack — training neural networks, building LLM and RAG applications with LangChain, LangGraph, and MCP, and developing statistical and time series models (ARIMA, regression, decomposition) that turn messy, high-volume data into accurate predictions and forecasts. I care a lot about the engineering underneath, from ETL pipelines in Python and SQL to cloud infrastructure on AWS and Azure, and about turning research code into systems that actually hold up in production.

Check out some of my photography work on VSCO.

About this site

Welcome to my home on the internet. This site functions as a blog/portfolio, a place to share code and thoughts. Opinions of my own.

I learnt how to build this site from the most awesome people in the community:

Experience

Data Scientist @ Agency for Persons with Disabilities — State of Florida
June 2025 – Present
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Analyze millions of transactional records across 60K+ clients and $200M+ in monthly spending, using exploratory and statistical analysis to surface anomalies, utilization trends, data inconsistencies, and operational patterns that inform financial and service decisions.
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Develop spending and budget forecasting models with ARIMA, regression, moving averages, and time series decomposition, generating projections that typically land within 5–10% of actual expenditures to support budgeting, rate decisions, and strategic planning.
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Model reimbursement rate scenarios across 22+ service areas, quantifying projected financial impact under alternative rates and translating historical spending and utilization patterns into data-driven recommendations for leadership.
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Engineer 40+ automated ETL and analytics pipelines in Python, SQL Server, and Azure Data Warehouse, processing 300K+ records and enabling scalable reporting, forecasting, and anomaly analysis.
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Re-engineered statistical and reporting workflows using Python, SQL, SPSS, and Power BI, cutting analysis turnaround time by 75% and SQL processing time by 83%, while delivering stakeholder-facing dashboards and ad hoc analyses.
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AI/ML Researcher @ Florida State University
June 2024 – September 2024
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Fine-tuned and benchmarked NequIP, an equivariant neural network, using transfer learning across 11,000+ material structures — tuning hyperparameters and custom MAE/MSE weighted loss functions to improve prediction consistency and reduce validation error by ~15%.
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Built reproducible Python, Docker, MLflow, and HPC workflows for data preparation, training, experiment tracking, inference, and evaluation, incorporating Neo4j to model relationships within structured scientific data and make experiments faster and repeatable.
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Designed controlled experiments across multiple model architectures using statistical hypothesis testing, A/B comparisons, and out-of-sample validation to identify the architecture that carried forward into subsequent models.
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Software Developer @ S&P Global
January 2022 – August 2023
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Led the modernization of legacy .NET document-processing workflows — researching and evaluating open-source Python OCR and document-processing technologies, then translating existing requirements into a scalable Python extraction platform and cutting licensing costs by 80%.
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Mentored a 5-person engineering team on Python data extraction and pipeline development while contributing to the architecture and production rollout of systems processing 10,000+ financial, energy, and automotive documents per day at 95% extraction accuracy.
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Engineered fault-tolerant AWS/Docker data pipelines with event-driven ingestion, automated retries, structured logging, and validation, reducing manual extraction effort by over 90% and enabling unattended data capture.
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Built OCR and CNN-based classification workflows with Tesseract and TensorFlow to turn unstructured financial filings, earnings information, energy specifications, and automotive documents into structured datasets for downstream analytics.
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Designed modular Python frameworks and cloud data workflows using AWS S3, Athena, BigQuery, REST APIs, CDC-based updates, GitHub Actions CI/CD, and 80% test coverage, improving scalability, data quality, and deployment reliability.
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Software Developer Intern @ LG Electronics
May 2021 – August 2021
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Developed real-time drowsiness detection and logistics tracking systems using Python, OpenCV, YOLO, CNNs, REST APIs, and PostgreSQL, hitting 90% detection accuracy and reducing package sorting time by 25%.
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Earned 3rd place in LG's internal Ideathon for the logistics tracking system.
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Software Developer Intern @ ITC Infotech
January 2021 – March 2021
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Developed Python Flask REST APIs with MySQL for master-data management, role-based access control, and automated product tracking workflows, reducing manual workload by 30%.
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Education

Masters in Data Science @ Florida State University
Aug 2023 – May 2025
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Cumulative GPA: 4/4
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Coursework: Statistics, Mathematics, Research, LLMs, Analytics, AI, Databases, Big Data, Business and Finance
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Bachelors in Computer Science @ Christ University
Aug 2018 – May 2022
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Cumulative GPA: 3.85/4
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Coursework: Data Structures, Operating System, Software Architecture, Programming, Networking, Communication, SDLC
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Skills

AI/ML
LLMsRAGMCPAI AgentsLangChainLangGraphLlamaIndexPyTorchTensorFlowscikit-learnClaudeCodexGeminiCohereOllamaPineconeSupabaseW&BMLflow
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Statistics & Forecasting
Time Series ForecastingARIMAGARCHRegressionDecompositionHypothesis TestingA/B TestingPredictive AnalyticsRSPSSSAS
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Quantitative Finance
Market ResearchEquity AnalysisDerivativesOptions PricingGreeksVolatilityFinancial ModelingAlpha Research
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Data Engineering & Infrastructure
PythonSQLPostgreSQLMySQLOracleSQL ServerMongoDBRedisCassandraNeo4jDuckDBSnowflakeDelta LakeAWSGCPAzureKubernetesDockerTerraformAirflowdbtKafkaHadoopSparkGitGitHub ActionsCI/CDLinuxBashPower BI
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