OnPoint Insights
Lead Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Lead Data Scientist with a contract length of "Unknown," offering a pay rate of "Unknown." Key skills include predictive modeling, NLP, Azure, and Databricks. Requires 5+ years in Data Science and strong communication abilities.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
October 10, 2025
🕒 - Duration
Unknown
-
🏝️ - Location
Unknown
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Raleigh, NC
-
🧠 - Skills detailed
#Data Science #Azure #Azure cloud #TensorFlow #Regression #Spark (Apache Spark) #Statistics #Python #Mathematics #Cloud #Predictive Modeling #A/B Testing #Pandas #Sentiment Analysis #"ETL (Extract #Transform #Load)" #Azure SQL #Azure Machine Learning #Libraries #Classification #Databricks #Deployment #Visualization #PySpark #Data Lake #PyTorch #Monitoring #Leadership #Reinforcement Learning #ML (Machine Learning) #NLP (Natural Language Processing) #Data Engineering #Data Pipeline #Clustering #Deep Learning #SQL (Structured Query Language) #Computer Science #SpaCy
Role description
Key Responsibilities
• Lead the development and deployment of predictive and prescriptive models to optimize business outcomes across multiple domains.
• Apply causal inference and statistical analysis techniques (e.g., propensity score matching, A/B testing, structural equation modeling, synthetic controls) to uncover cause–effect relationships and support decision-making.
• Develop and operationalize NLP solutions for unstructured text data, including entity extraction, text classification, sentiment analysis, and topic modeling.
• Build, optimize, and maintain large-scale data pipelines and analytical workflows in Azure and Databricks environments.
• Collaborate with cross-functional teams (engineering, product, business stakeholders) to translate business problems into data science solutions.
• Communicate insights and recommendations clearly through visualizations, reports, and presentations to technical and non-technical audiences.
• Contribute to building best practices in model development, deployment, and monitoring.
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
Required Qualifications
• 5+ years of professional experience in Data Science or Advanced Analytics.
• Strong expertise in predictive modeling, prescriptive analytics, and statistical methods (regression, classification, clustering, optimization).
• Hands-on experience with causal analysis (e.g., causal inference frameworks, experiments, quasi-experiments).
• Proficiency in Natural Language Processing (NLP) using modern libraries (e.g., HuggingFace, Spark NLP, spaCy).
• Proficient in Python (pandas, scikit-learn, statsmodels, PySpark) and SQL.
• Advanced knowledge of Databricks for large-scale data engineering and machine learning workflows.
• Strong experience with Azure Cloud Services (e.g., Azure Machine Learning, Azure Data Lake, Fabric, Azure SQL, Functions).
• Solid understanding of MLOps practices (versioning, CI/CD for ML, monitoring, reproducibility).
• Excellent communication skills with ability to present findings to both technical and executive stakeholders.
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
Preferred Qualifications
• Advanced degree (MS or PhD) in Data Science, Computer Science, Statistics, Applied Mathematics, or related field.
• Experience with deep learning frameworks (TensorFlow, PyTorch) for NLP and other advanced modeling tasks.
• Exposure to healthcare, life sciences, or other regulated industries where causal analysis and interpretability are critical.
• Familiarity with reinforcement learning, prescriptive optimization, or advanced decision sciences.
• Contributions to open-source projects, publications, or thought leadership in the data science community.
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
Key Responsibilities
• Lead the development and deployment of predictive and prescriptive models to optimize business outcomes across multiple domains.
• Apply causal inference and statistical analysis techniques (e.g., propensity score matching, A/B testing, structural equation modeling, synthetic controls) to uncover cause–effect relationships and support decision-making.
• Develop and operationalize NLP solutions for unstructured text data, including entity extraction, text classification, sentiment analysis, and topic modeling.
• Build, optimize, and maintain large-scale data pipelines and analytical workflows in Azure and Databricks environments.
• Collaborate with cross-functional teams (engineering, product, business stakeholders) to translate business problems into data science solutions.
• Communicate insights and recommendations clearly through visualizations, reports, and presentations to technical and non-technical audiences.
• Contribute to building best practices in model development, deployment, and monitoring.
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
Required Qualifications
• 5+ years of professional experience in Data Science or Advanced Analytics.
• Strong expertise in predictive modeling, prescriptive analytics, and statistical methods (regression, classification, clustering, optimization).
• Hands-on experience with causal analysis (e.g., causal inference frameworks, experiments, quasi-experiments).
• Proficiency in Natural Language Processing (NLP) using modern libraries (e.g., HuggingFace, Spark NLP, spaCy).
• Proficient in Python (pandas, scikit-learn, statsmodels, PySpark) and SQL.
• Advanced knowledge of Databricks for large-scale data engineering and machine learning workflows.
• Strong experience with Azure Cloud Services (e.g., Azure Machine Learning, Azure Data Lake, Fabric, Azure SQL, Functions).
• Solid understanding of MLOps practices (versioning, CI/CD for ML, monitoring, reproducibility).
• Excellent communication skills with ability to present findings to both technical and executive stakeholders.
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
Preferred Qualifications
• Advanced degree (MS or PhD) in Data Science, Computer Science, Statistics, Applied Mathematics, or related field.
• Experience with deep learning frameworks (TensorFlow, PyTorch) for NLP and other advanced modeling tasks.
• Exposure to healthcare, life sciences, or other regulated industries where causal analysis and interpretability are critical.
• Familiarity with reinforcement learning, prescriptive optimization, or advanced decision sciences.
• Contributions to open-source projects, publications, or thought leadership in the data science community.
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
