Senior Data Scientist

Senior Data Scientist Job at a Glance Location: Richmond, VA (Alternate weeks in office and remote; 5 days in office, 5 days remote, repeating. Local drive-in candidate only; no 100% remote) Duration: 12 months Labor Type: Technical Business Unit: Data Analytics Interview Process: Teams – Camera ON Industry Preference: Regulated industry In this advanced level role, the Senior Data Science Analyst works independently on the most complex programs. Researches and applies knowledge from existing and emerging data science principles, theories and practices to identify and solve complex analytic problems using established procedures, tools and platforms. Conducts requirements gathering and design sessions and defines and documents the scope and objectives for the business use case/solution. Performs detailed analysis and feature engineering on data. Works at a high technical level in all phases of data analysis, design, development and support of analytic solutions including design and development of data structures, data integration processes and user interfaces to illustrate the analytical insights. Guides and/or leads less experienced Data Science Analysts analytic projects, as needed. Delivers oral briefs, presentations and insights from analysis performed or solutions developed. Tests, compares and validates the results from Machine Learning models before implementing the solution. Works company-wide, in multi-platform environments, on multiple project assignments. Responsibilities Research and apply knowledge from existing and emerging data science principles, theories and practices to identify and solve complex analytic problems using established procedures, tools and platforms. Conduct requirements gathering and design sessions and define and document the scope and objectives for the business use case/solution. Perform detailed analysis and feature engineering on data. Work at a high technical level in all phases of data analysis, design, development and support of analytic solutions including design and development of data structures, data integration processes and user interfaces to illustrate the analytical insights. Guide and/or lead less experienced Data Science Analysts analytic projects, as needed. Deliver oral briefs, presentations and insights from analysis performed or solutions developed. Test, compare and validate the results from Machine Learning models before implementing the solution. Design machine learning projects to address business problems determined by consultation with business partners. Work on a variety of datasets, including both structured and unstructured data. Create interpretable visualizations that tell a story and paint a vision. Qualifications MUST have 5 years of experience in Data Science using R/Python etc. on Hadoop platform. Strong skills in statistical application prototyping with expert knowledge in R and/or Python development. Deep knowledge of machine learning, data mining, statistical predictive modeling, and extensive experience applying these methods to real world problems. Extensive experience in Predictive Modeling and Machine Learning: Classification, Regression & Clustering. Experience with automated testing, versioning, and deployment workflows (e.g., MLflow, Dataiku, or similar). Experience with using or monitoring of ML models, including model drift detection, performance tracking, reproducibility, and scalable production architecture. Experience with developing reports and apps with tools like RShiny to allow stakeholders to interact with data. Understanding and experience working on Big Data Ecosystems is preferred: Hadoop, HDFS, Hive, Sqoop, Spark: pySpark, SparkR, SparkSQL, Jupyter & Zeppelin notebooks. Understanding and/or experience with data engineering is a plus. Experience with cloud technologies (AWS, Azure, GCP, Snowflake) is a big plus. Strong communication skills both verbal and written. Ability to lead, collaborate, or work effectively in a variety of teams, including multi-disciplinary teams. Minimum of High School Diploma or Equivalency. Bachelors or higher preferred – Discipline: Computer Science, Information Systems, Mathematics. About the Client The client is a large, regulated energy organization supporting enterprise-wide operations across generation, transmission, distribution, and corporate functions. The Data Analytics team partners with business units across the company to deliver advanced analytics, predictive modeling, and machine learning solutions that support operational reliability, regulatory compliance, and strategic decision-making. The environment is highly structured and compliance-driven, requiring strong documentation, validation, and governance practices within a complex, multi-platform ecosystem. #INDGEN #ZR