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Senior Data Engineer highly proficient in SAS and R, delivering statistical and epidemiologic analyses, cohort creation, and longitudinal real-world evidence pipelines across e-commerce and healthcare data (claims and EHR). Experienced with OMOP Common Data Model and OHDSI tooling, including automated TFL/reporting, data quality frameworks, and protocol/SAP-aligned analytics deliverables. Former Data Scientist and Data Engineer in AI/NLP and fintech domains, building HIPAA-aligned pipelines, NLP/transformer models, RAG systems, and low-latency streaming architectures. Strong focus on data rigor, auditability, reproducibility, and production-ready systems using cloud and modern engineering practices.…Senior Data Engineer highly proficient in SAS and R, delivering statistical and epidemiologic analyses, cohort creation, and longitudinal real-world evidence pipelines across e-commerce and healthcare data (claims and EHR). Experienced with OMOP Common Data Model and OHDSI tooling, including automated TFL/reporting, data quality frameworks, and protocol/SAP-aligned analytics deliverables. Former Data Scientist and Data Engineer in AI/NLP and fintech domains, building HIPAA-aligned pipelines, NLP/transformer models, RAG systems, and low-latency streaming architectures. Strong focus on data rigor, auditability, reproducibility, and production-ready systems using cloud and modern engineering practices.

Adam Ringwood

Data Engineer, Data Scientist, Software Engineer, +2

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Senior Data Engineer highly proficient in SAS and R, delivering statistical and epidemiologic analyses, cohort creation, and longitudinal real-world evidence pipelines across e-commerce and healthcare data (claims and EHR). Experienced with OMOP Common Data Model and OHDSI tooling, including automated TFL/reporting, data quality frameworks, and protocol/SAP-aligned analytics deliverables. Former Data Scientist and Data Engineer in AI/NLP and fintech domains, building HIPAA-aligned pipelines, NLP/transformer models, RAG systems, and low-latency streaming architectures. Strong focus on data rigor, auditability, reproducibility, and production-ready systems using cloud and modern engineering practices.…Senior Data Engineer highly proficient in SAS and R, delivering statistical and epidemiologic analyses, cohort creation, and longitudinal real-world evidence pipelines across e-commerce and healthcare data (claims and EHR). Experienced with OMOP Common Data Model and OHDSI tooling, including automated TFL/reporting, data quality frameworks, and protocol/SAP-aligned analytics deliverables. Former Data Scientist and Data Engineer in AI/NLP and fintech domains, building HIPAA-aligned pipelines, NLP/transformer models, RAG systems, and low-latency streaming architectures. Strong focus on data rigor, auditability, reproducibility, and production-ready systems using cloud and modern engineering practices.

Available to hire

Senior Data Engineer highly proficient in SAS and R, delivering statistical and epidemiologic analyses, cohort creation, and longitudinal real-world evidence pipelines across e-commerce and healthcare data (claims and EHR). Experienced with OMOP Common Data Model and OHDSI tooling, including automated TFL/reporting, data quality frameworks, and protocol/SAP-aligned analytics deliverables.

Former Data Scientist and Data Engineer in AI/NLP and fintech domains, building HIPAA-aligned pipelines, NLP/transformer models, RAG systems, and low-latency streaming architectures. Strong focus on data rigor, auditability, reproducibility, and production-ready systems using cloud and modern engineering practices.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Language

Afar

Advanced

Javanese

Intermediate

Work Experience

Senior Data Engineer at Wayfair

January 1, 2021 - Present

Led e-commerce data engineering initiatives supporting large-scale cohort studies, longitudinal analysis, and statistical modeling. Built and optimized pipelines for cohort creation, baseline and outcome variable generation, improving cohort generation efficiency by ~40%. Implemented automated data quality validation to ensure accuracy and consistency for longitudinal research. Integrated commercial claims and EHR data (including MarketScan/IQVIA PharMetrics concepts) to enable comprehensive real-world evidence analytics. Programmed statistical analyses including regression and survival/time-to-event models in SAS and R, and contributed to protocol/SAP development for scientific rigor. Developed and automated TFLs (tables/figures/listings), reducing reporting cycle time by ~30%. Implemented OMOP Common Data Model and OHDSI tooling for standardized analysis and deliverables, collaborating with cross-functional teams to produce high-quality, auditable, reproducible outputs.

Data Scientist at Tempus AI

May 1, 2019 - December 31, 2020

Developed AI/ML and healthcare analytics platforms for precision medicine and clinical decision support. Built clinical NLP systems for pathology reports, physician notes, and genomic documentation using transformer architectures (e.g., BERT/RoBERTa) for medical entity extraction. Created predictive models for patient stratification and treatment outcome prediction with feature engineering pipelines across EHR and genomic sources. Designed HIPAA-compliant pipelines integrating EHR/lab/genomic data, implementing lineage tracking, auditability, and governance. Built retrieval-augmented clinical knowledge assistant (RAG) using medical literature and guidelines, with vector-based semantic search, prompt optimization, and evaluation to mitigate hallucinations; deployed and monitored inference/retrieval pipelines for production use.

Data Engineer at Enova International

August 1, 2017 - April 30, 2019

Built enterprise-scale fintech data platforms supporting digital lending, fraud detection, credit risk analytics, and operational intelligence. Engineered Kafka-based streaming platforms for lending/payment events and developed Spark Streaming workflows to support low-latency fraud detection and risk evaluation. Designed fault-tolerant architectures for mission-critical systems. Developed feature pipelines for credit scoring/fraud prevention models, built governed datasets and analytical data marts, and partnered with risk teams to improve data availability and quality.