Senior Data Scientist / Data Analyst

Overview

On Site
Depends on Experience
Contract - W2
Contract - 12 Month(s)
No Travel Required

Skills

A/B Testing
Amazon S3
Amazon SageMaker
Apache Hadoop
Cloud Computing
Clustering
Data Analysis
Data Integrity
Data Engineering
Data Visualization
Good Clinical Practice
Data Science
Collaboration
Business Intelligence
Communication
Computer Science
Apache Kafka
Analytics
Extract
Transform
Load
Finance
Flask
Forecasting
Machine Learning (ML)
Mentorship
Apache Spark
Health Care
Artificial Intelligence
Analytical Skill
Dashboard
Database
Microsoft Power BI
Docker

Job Details

Job Title: Senior Data Scientist / Data Analyst

Experience Required: 10+ Years
Location: Franklin, TN
Employment Type: Full-Time (only W2)

Job Summary:

We are seeking a highly experienced and results-driven Senior Data Scientist / Analyst to lead strategic data initiatives, apply cutting-edge analytics, and generate actionable insights that drive business impact. The ideal candidate has over 10 years of experience across data science, analytics, machine learning, and business intelligence, with a deep understanding of statistical methods, big data platforms, and cloud ecosystems.

Key Responsibilities:

  • Lead the design, development, and deployment of end-to-end data solutions.

  • Collaborate with cross-functional teams (product, marketing, engineering) to translate business goals into analytical solutions.

  • Perform advanced data analysis, predictive modeling, segmentation, and time-series forecasting.

  • Build and optimize machine learning models using frameworks like Scikit-learn, TensorFlow, or PyTorch.

  • Develop dashboards and automated reports using Power BI, Tableau, or Looker.

  • Create and maintain ETL pipelines, ensuring data integrity and quality.

  • Conduct A/B testing and statistical hypothesis testing to evaluate changes and optimizations.

  • Lead and mentor junior analysts and data scientists.

  • Communicate complex findings to stakeholders through storytelling and visualization.

Core Skills & Technologies:

< data-start="1821" data-end="1853"> Programming & Tools:</>

  • Python, R, SQL, Scala (preferred)

  • Jupyter Notebooks, VS Code, Git, Docker

< data-start="1941" data-end="1985"> Data Science & Machine Learning:</>

  • Regression, Classification, Clustering, NLP, Deep Learning

  • Model deployment (Flask/FastAPI, MLflow, ONNX)

  • Feature engineering, model tuning (GridSearch, Optuna)

< data-start="2154" data-end="2193"> Big Data & Cloud Platforms:</>

  • Spark, Hadoop, Kafka, Databricks

  • AWS (S3, Glue, SageMaker), Azure (Data Factory, ML Studio), Google Cloud Platform (BigQuery, Vertex AI)

< data-start="2346" data-end="2388"> Data Visualization & BI Tools:</>

  • Tableau, Power BI, Looker

  • Plotly, Seaborn, Matplotlib

< data-start="2460" data-end="2501"> Databases & Data Engineering:</>

  • PostgreSQL, MySQL, Oracle, MongoDB, Snowflake

  • Airflow, DBT, Informatica (for ETL orchestration)

Qualifications:

  • Bachelor s or Master s in Computer Science, Statistics, Data Science, or related field (Ph.D. is a plus)

  • Proven experience delivering high-impact data projects across domains (e.g., finance, healthcare, retail, tech)

  • Strong communication, stakeholder management, and leadership skills

  • Published research, patents, or open-source contributions is a plus

Preferred Certifications (Optional but Valuable):

  • Google Professional Data Engineer

  • AWS Certified Machine Learning

  • Microsoft Azure Data Scientist Associate

  • Tableau/Power BI Certification

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.