Senior Data Scientist – AI/ML & BI, Hybrid (DC)

Seneca Resources Company, LLC; Virginia; Hybrid; USD 120,000 - 170,000; Full time

Benefits offered by this job

Health coverage

Dental coverage

Vision coverage

401(k) retirement plans

Job summary

Seneca Resources is seeking an experienced Data Scientist III to support advanced data analytics, AI/ML, and BI initiatives in a complex enterprise setting. This role focuses on transforming data into actionable insights and scalable solutions.

You will work across data engineering, analytics, visualization, and cloud platforms (AWS/Azure, Databricks), building ETL/ELT pipelines, dashboards, and production-ready models while briefing leadership and stakeholders.

Qualifications

• Experience designing and deploying ML/AI solutions in enterprise data environments.
• Ability to translate complex data into actionable insights for stakeholders.
• Strong communication and technical documentation skills.

Responsibilities

• Extract, clean, and analyze structured and unstructured data from multiple sources.
• Develop ML/AI solutions, including model training, evaluation, deployment, and maintenance.
• Create interactive dashboards and reports using Power BI and BI platforms.
• Collaborate with IT, data engineers, and business owners to deliver analytics solutions.

Skills

Python

SQL

R

JavaScript

Machine Learning

NLP

Data Mining

Statistical Modeling

Communication

Independent Work

Education

Bachelor's degree in Computer Science, Information Technology, Data Analytics, Data Science, Mathematics, Statistics, or related field

Tools

Power BI

Databricks

AWS

Azure

Data Factory

Data Lake

Data Lakehouse

Job description

Seneca Resources is seeking an experienced Data Scientist III to support advanced data analytics, AI/ML, and BI initiatives in a complex enterprise setting. This role focuses on transforming data into actionable insights and scalable solutions.

You will work across data engineering, analytics, visualization, and cloud platforms (AWS/Azure, Databricks), building ETL/ELT pipelines, dashboards, and production-ready models while briefing leadership and stakeholders.