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Dennis Jose

@dennisjose

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Data Scientist focused on production LLM pipelines, trustworthy analytics, and measurable ETL-to-dashboard impact.

United States

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What I'm looking for

I’m looking for a team where I can build and evaluate production GenAI and data pipelines end-to-end—prioritizing reproducibility, governance, and measurable business impact through ETL, dashboards, and uncertainty-aware modeling.

I build production-ready data and AI systems that turn ambiguous business needs into reliable analytics. I specialize in GenAI and predictive workflows that I can ship, evaluate, and govern—so stakeholders can act with confidence.

At Northeastern University, I deployed LLM pipelines using Anthropic APIs, iterating through prompt engineering and evaluation cycles until outputs met production reliability standards for institutional reporting. I also built automated Snowflake data lake ETL pipelines and self-serve Tableau dashboards with layered data modeling, cutting reporting turnaround by 93% and enabling operational decisions driven by stakeholder needs.

I embed statistical anomaly detection, data quality validation, and feature engineering into every pipeline to maintain governance compliance and schema consistency. I pair hypothesis-driven analysis with consultative collaboration to translate requirements into structured GenAI and predictive analytics solutions.

Earlier, I advanced machine learning for clinical image classification by evaluating deep models (ResNet, DenseNet, Vision Transformer) across diagnostic categories, handling extreme class imbalance with Dice+BCE and progressive fine-tuning. I also gained strong backend fundamentals at Oracle Financial Services, developing Java/Python/PLSQL systems for high-volume transaction processing and improving throughput by 30%, while reducing peak-load query execution time by 20% through automated batch-processing logic.

Experience

Work history, roles, and key accomplishments

Data Scientist (Admin Fellow)

Northeastern University

Sep 2025 - Apr 2026 (7 months)

Deployed production LLM pipelines using Anthropic APIs, iterating on prompt engineering and evaluation to meet institutional reporting reliability standards; built Snowflake ETL pipelines and self-serve Tableau dashboards, cutting reporting turnaround by 93%. Embedded statistical anomaly detection, data quality validation, and feature engineering into each pipeline to ensure governance compliance

Anthropic Prompt Engineering LLM Evaluation Tableau Anomaly Detection Data Validation Feature Engineering GenAI

Machine Learning Research Fellow

Zeta Surgical X

Sep 2025 - Dec 2025 (3 months)

Designed and evaluated deep learning models (ResNet, DenseNet, Vision Transformer) for clinical image classification across seven diagnostic categories, performing systematic error analysis in an agile R&D environment. Built a full prototype pipeline from data ingestion through feature engineering, model training, and evaluation, resolving extreme class imbalance (0.3% positive rate) using Dice+BC

ResNet DenseNet Vision Transformer Dice+BCE Loss Fine Tuning Model Evaluation Ablation Studies

Associate Consultant

Oracle Financial Services

Jul 2023 - Jul 2024 (1 year)

Developed backend transaction-processing systems using Java, Python, and PL/SQL, optimizing query performance to improve system throughput by 30%. Built automated batch-processing pipelines that reduced query execution time by 20% during peak loads and collaborated with engineering and QA teams to debug production code, implement performance improvements, and maintain system reliability.