Senior Data Scientist

We are seeking a highly skilled and hands-on Senior Data Scientist to join our team in Richmond, VA. In this advanced role, you will work independently on complex programs, leading the charge in identifying and solving intricate analytic problems. You will leverage your deep expertise in data science to guide projects from conception to production, working closely with multi-disciplinary teams to deliver actionable insights.

This role requires a candidate who is not only a master of predictive modeling but also has a strong command of the entire machine learning lifecycle, from development on Big Data platforms to deployment, monitoring, and visualization. This is a hybrid position, requiring the selected candidate to be local and able to work in the Richmond office on alternating weeks (5 days in office, 5 days remote).

Top Required Skills & Experience

To be successful in this role, you MUST have demonstrable experience in the following areas:

1. Advanced Analytics & Big Data: Extensive hands-on experience with R/Python for data science on the Hadoop platform (including HDFS, Hive, Spark).
2. MLOps & Model Lifecycle: Proven experience with automated testing, versioning, and deployment workflows using tools like MLflow, Dataiku, or similar .
3. Model Monitoring: Experience in monitoring ML models in production, including model drift detection, performance tracking, and ensuring reproducibility in a scalable architecture.
4. Data Visualization & Communication: Experience developing interactive reports and applications with tools like RShiny to allow stakeholders to explore and interact with data.
5. Core Data Science Expertise: Deep, applied experience with Predictive Modeling and Machine Learning techniques, specifically Classification, Regression, and Clustering .

Key Responsibilities

• Design and execute machine learning projects to address complex business problems, consulting with partners to define scope and objectives.
• Perform detailed analysis and feature engineering on diverse datasets, including both structured and unstructured data.
• Develop, test, and validate machine learning models, comparing results to ensure accuracy and business value before implementation.
• Implement and manage the full lifecycle of ML models, including automated deployment, versioning, and ongoing monitoring for drift and performance.
• Build and maintain data structures and integration processes to support analytic solutions.
• Create compelling and interpretable visualizations and applications (e.g., using RShiny) that communicate insights and tell a clear story to stakeholders.
• Guide and lead less experienced data science analysts on complex projects.
• Deliver oral briefings, presentations, and written reports on analysis performed and solutions developed.

Qualifications & Requirements

Required Experience & Education:

• Minimum 5 years of experience in Data Science, specifically using R/Python on a Hadoop platform .
• Education: Bachelor's degree or higher preferred in Computer Science, Information Systems, Mathematics, or a related field. (High School Diploma or Equivalency is the minimum requirement).

Technical Proficiency:

• Expert-level knowledge in statistical application prototyping with R and/or Python.
• Deep understanding of machine learning, data mining, and statistical predictive modeling (Classification, Regression, Clustering).
• Experience working within the Hadoop ecosystem (HDFS, Hive, Sqoop, Spark) is strongly preferred.
• Familiarity with cloud technologies (AWS, Azure, GCP) and cloud data platforms like Snowflake is a significant plus.
• Experience or understanding of data engineering principles is a plus.

Soft Skills & Team Fit:

• Strong Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical audiences.
• Collaborative & Independent: Ability to work effectively in multi-disciplinary teams, as well as independently lead complex projects.
• Leadership: Proven ability to guide and mentor junior team members.

Preferred Candidate Profile:

• Location: Local to Richmond, VA, or able to drive in for the required hybrid schedule.
• Industry: Experience in a regulated industry (e.g., finance, energy, healthcare) is highly preferred.