[Remote] Senior Data Scientist - Joplin, MO/Bentonville, AR/Miami, OK/Pittsburg, KS/Dallas, TX
Note: The job is a remote job and is open to candidates in USA. Dice is seeking an experienced Data Scientist to design, develop, and implement advanced analytical and machine learning solutions. The ideal candidate will leverage statistical modeling, predictive analytics, and data-driven methodologies to deliver actionable insights and support strategic business decisions.
Responsibilities
- Develop and deploy predictive and statistical models to solve complex business problems
- Perform data collection, cleansing, transformation, and exploratory data analysis
- Build machine learning models and optimize model performance
- Analyze large datasets to identify trends, patterns, and actionable insights
- Develop dashboards, reports, and visualizations for business stakeholders
- Collaborate with business teams, analysts, and engineers to understand requirements and deliver analytical solutions
- Validate and monitor model accuracy and performance
- Present findings and recommendations to technical and non-technical stakeholders
- Support end-to-end data science lifecycle activities from data preparation through model deployment
Skills
- Strong experience in Data Science and Advanced Analytics
- Expertise in Machine Learning Algorithms
- Experience with Python and statistical analysis
- Strong knowledge of Data Modeling and Predictive Analytics
- Experience with data manipulation and feature engineering
- Knowledge of SQL and database concepts
- Experience with data visualization and reporting tools
- Ability to work with large and complex datasets
- Strong analytical and problem-solving skills
- Experience with deep learning frameworks and AI technologies
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform
- Experience with big data technologies and distributed computing frameworks
- Master's degree or higher in Computer Science, Statistics, Mathematics, Data Science, or a related field
- Experience working in Agile environments
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