Available to hire
I’m Darshil Gohel, a Senior Data Scientist and Machine Learning Engineer with over a decade of experience delivering scalable AI/ML solutions across healthcare, media, federal, and telecom sectors. I specialize in end-to-end ML systems, NLP/LLMs, and Generative AI, with a strong focus on responsible AI, statistical rigor, and measurable business impact. I thrive leading cross-functional teams, mentoring junior talent, and translating complex business problems into data-driven strategies.
I’ve built and deployed production-grade ML and NLP solutions, streamlined data pipelines, and implemented MLOps practices across cloud environments. My work combines hands-on modeling with practical deployment, monitoring, and governance to ensure scalable, ethical, and impactful AI in healthcare operations, marketing analytics, and enterprise data platforms.
Skills
Experience Level
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Language
English
Fluent
Work Experience
Senior Data Scientist / Machine Learning Engineer at Nielsen
March 1, 2020 - November 14, 2025Led design and deployment of advanced ML models for healthcare, marketing, and telecom; built end-to-end pipelines from data preprocessing to model training, deployment, and monitoring using AWS SageMaker, Databricks, PySpark, and TensorFlow. Implemented NLP solutions (NER, semantic search) and applied Generative AI (GPT-4, BERT) to conversational AI and content summarization, improving operational efficiency. Automated data pipelines with Databricks, AWS Glue, and Snowflake, cutting reporting latency by 60%. Drove A/B testing, causal inference, and ROI improvements; mentored 10+ data scientists and engineers; presented model reviews and ROI analyses to leadership.
Lead Data Analyst / ML Developer at Axxess
March 1, 2020 - March 1, 2020Led cross-functional teams of up to 15 data scientists, ML engineers, and analysts to deliver scalable AI/ML solutions across healthcare, retail, and consumer sectors. Designed end-to-end ML pipelines using MLflow, SageMaker, TensorFlow, and Kubeflow; accelerated model iteration and deployment times. Automated regulatory document processing using BERT and AWS Comprehend, reducing manual review time by 80% across 5,000+ documents for federal clients (FDA, NIH). Implemented model monitoring and drift detection; mentored 6+ engineers; guided product decisions on ML features; integrated insights into Looker/Tableau dashboards to inform executives.
Data Analytics Intern / ML Developer at Idibri
December 1, 2017 - December 1, 2017Reduced acoustic data analysis time by 33% by building a web-based analytics tool using R Shiny, ggplot2, and Plotly; created interactive dashboards for real-time sound pattern analysis; collaborated with engineers to tailor analytics for acoustic design.
Project Engineer at Wipro Technologies
July 1, 2016 - July 1, 2016Reduced operating asset costs by ~30% for telecom clients by developing an end-to-end asset lifecycle management system using IBM Maximo, Python, Java, SQL/PLSQL, and Tableau dashboards; built robust data pipelines for cleansing, extraction, transformation, and migration; mentored 6 junior engineers; delivered KPI dashboards to track 200K+ assets in real time.
Intern – Data Integration at Wipro Technologies
May 1, 2013 - May 1, 2013Implemented an AIDC solution using RFID hardware, Arduino, and MATLAB; integrated hardware-generated data with IBM Maximo 7.5 via web services; improved backend data handling and system architecture end-to-end.
Data Analytics Intern at Idibri
December 1, 2017 - December 1, 2017Reduced acoustic data analysis time by 33% by building a web-based analytics tool using R Shiny, ggplot2, and Plotly. Performed data wrangling in R and Python for time-domain and frequency-domain acoustic data. Built interactive dashboards enabling consultants to explore real-time sound patterns. Collaborated with engineers to tailor visual tools that improved client presentations and technical documentation. Contributed to scalable internal analytics platform.
Lead Data Analyst | ML Developer at Axxess
August 1, 2018 - March 1, 2020Led cross-functional teams of up to 15 data scientists, ML engineers, and analysts to deliver scalable AI/ML solutions across healthcare, retail, and consumer sectors, ensuring compliance and operational readiness. Built end-to-end ML pipelines with MLflow, SageMaker, TensorFlow, and Kubeflow; deployed real-time and batch inference on enterprise platforms. Automated regulatory document processing using BERT and AWS Comprehend, reducing manual review time for federal clients and enabling rapid regulatory insights. Implemented model monitoring, drift detection, and production-grade deployment. Mentored junior engineers and advanced the adoption of generative AI for chatbots, intelligent search, and content summarization.
Project Engineer at Wipro Technologies
July 1, 2013 - July 1, 2016Reduced operating asset costs by ~30% for telecom clients by developing and deploying an end-to-end asset lifecycle management system using IBM Maximo, Python, Java, SQL/PLSQL, and Tableau dashboards; designed robust data pipelines for cleansing, extraction, transformation, and migration tasks; mentored junior engineers and delivered scalable solutions in Agile environments.
Senior Data Scientist / Machine Learning Engineer at Nielsen (Tampa, FL)
March 1, 2020 - PresentLed design and deployment of advanced ML models for healthcare, marketing, and telecom; applied supervised and unsupervised learning (XGBoost, Random Forest, Logistic Regression) to drive business impact (e.g., increasing sales conversion efficiency by 20%). Built end-to-end ML pipelines (EDA, preprocessing, training, deployment) using AWS SageMaker, MLflow, Kubeflow, and PySpark; developed NLP solutions including named entity recognition and semantic search using spaCy and NLTK; automated data pipelines with Databricks, AWS Glue, and Snowflake; applied Generative AI (GPT-4, BERT) for conversational AI and content summarization; collaborated with RevOps, Finance, and Product; performed A/B testing and causal inference to optimize strategies; championed MLOps and model monitoring; mentored 10+ data scientists and engineers; delivered quarterly model reviews to leadership.
Lead Data Analyst | ML Developer at Axxess (Dallas/Fort Worth, TX)
August 1, 2018 - March 1, 2020Led cross-functional teams of up to 15 data scientists, ML engineers, and analysts; designed and deployed ML pipelines (MLflow, SageMaker, TensorFlow, Kubeflow); accelerated model iteration cycles by 40% and reduced deployment time from weeks to days. Built real-time and batch inference platforms using AWS S3, Glue, Athena, Spark, Snowflake; automated regulatory document processing using BERT and AWS Comprehend, reducing manual review time by 80% across 5,000+ documents for FDA and NIH. Built and integrated model monitoring and drift detection systems; mentored 6+ junior engineers; championed generative AI and LLMs for chatbots, intelligent search, and content summarization; advised product on ML trade-offs; promoted ethical AI and data governance; improved data quality and reduced survey errors; delivered scalable ETL pipelines and risk models for national benchmarks.
Education
Master of Science in Business Analytics at The University of Texas at Dallas
January 1, 2016 - June 1, 2018Bachelor of Technology in Electrical Engineering at Nirma University
July 1, 2009 - May 1, 2013Master's degree at The University of Texas at Dallas
January 1, 2016 - June 1, 2018Bachelor's degree of Technology at Nirma University
July 1, 2009 - May 1, 2013Master's degree, Business Analytics at The University of Texas at Dallas
January 1, 2016 - June 1, 2018Bachelor's degree of Technology, Electrical, Electronics at Nirma University
July 1, 2009 - May 1, 2013Master's degree in Business Analytics at The University of Texas at Dallas
January 1, 2016 - June 1, 2018Bachelor of Technology in Electrical & Electronics at Nirma University
July 1, 2009 - May 1, 2013Qualifications
Essentials of MLOps with Azure: Databricks MLflow and MLflow Tracking
August 1, 2024 - November 14, 2025Essentials of MLOps with Azure: Spark MLflow Models and Model Registry
August 1, 2024 - November 14, 2025MLOps Essentials: Model Deployment and Monitoring
August 1, 2024 - November 14, 2025Python for Data Science, AI & Development
April 1, 2024 - November 14, 2025Scala and Spark for Big Data and Machine Learning
April 1, 2018 - November 14, 2025Spark and Python for Big data with PySpark
March 1, 2018 - November 14, 2025Essentials of MLOps with Azure: 2 Databricks MLflow and MLflow Tracking
August 1, 2024 - November 14, 2025Essentials of MLOps with Azure: 4 Spark MLflow Models and Model Registry
August 1, 2024 - November 14, 2025MLOps Essentials: Model Deployment and Monitoring
August 1, 2024 - November 14, 2025Python for Data Science, AI & Development
April 1, 2024 - November 14, 2025Scala and Spark for Big Data and Machine Learning
April 1, 2018 - November 14, 2025Spark and Python for Big data with PySpark
March 1, 2018 - November 14, 2025Essentials of MLOps with Azure: 2 Databricks MLflow and MLflow Tracking
August 1, 2024 - December 15, 2025Essentials of MLOps with Azure: 4 Spark MLflow Models and Model Registry
August 1, 2024 - December 15, 2025MLOps Essentials: Model Deployment and Monitoring
August 1, 2024 - December 15, 2025Python for Data Science, AI & Development
April 1, 2024 - December 15, 2025Scala and Spark for Big Data and Machine Learning
April 1, 2018 - December 15, 2025Spark and Python for Big data with PySpark
March 1, 2018 - December 15, 2025Essentials of MLOps with Azure: 2 Databricks MLflow and MLflow Tracking
August 1, 2024 - December 15, 2025Essentials of MLOps with Azure: 4 Spark MLflow Models and Model Registry
August 1, 2024 - December 15, 2025MLOps Essentials: Model Deployment and Monitoring
August 1, 2024 - December 15, 2025Python for Data Science, AI & Development
April 1, 2024 - December 15, 2025Scala and Spark for Big Data and Machine Learning
April 1, 2018 - December 15, 2025Spark and Python for Big data with PySpark
March 1, 2018 - December 15, 2025Industry Experience
Healthcare, Government, Life Sciences, Media & Entertainment, Telecommunications, Software & Internet, Professional Services
Skills
Experience Level
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
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