Data Scientist – Associate, Experienced Level

• Collect and clean data from various sources while ensuring data quality
• Manipulate and transform data using SQL, Python, and R
• Apply statistical techniques and machine learning algorithms for exploratory data analysis
• Support development, validation, and deployment of machine learning and statistical models
• Develop understanding of delivering data science models in a production environment
• Create impactful visualizations to communicate findings
• Collaborate with stakeholders to understand business challenges and develop data-driven solutions
• Translate technical concepts into actionable insights
• Balance learning with practical application
• Understand project and team scope in relation to broader strategic initiatives
• Communicate findings to technical and non-technical audiences

• Bachelor’s degree in computer science, data science, statistics, math, or a related analytical concentration is required for the Associate Data Scientist level
• Other bachelor’s degrees with data science-relevant certifications will be considered
• Bachelor’s degree in computer science, data science, math, statistics, or a related analytical concentration for the Data Scientist level
• Minimum 3 years working as a data scientist or application developer for the Data Scientist level
• 2 years of experience with an MS or Ph.D. for the Data Scientist level
• Relevant certifications may be considered in lieu of a postgraduate degree in combination with years of experience
• Experience with SQL, Python, and R
• Knowledge of statistical analysis and machine learning algorithms
• Experience with data visualization tools
• Ability to develop, validate, and deploy machine learning and statistical models
• Ability to deliver data science models in a production environment
• Ability to communicate technical concepts and findings to technical and non-technical audiences

Proficient in data collection, cleaning, and manipulation using SQL, Python, and R, with a strong ability to apply statistical techniques and machine learning algorithms. Skilled in developing and deploying data science models in production environments and effectively communicating insights to diverse audiences.

• SQL
• Python
• R
• Machine Learning
• Data Visualization

• Data Collection
• Data Cleaning
• Statistical Analysis
• Machine Learning Algorithms
• Model Validation
• Model Deployment
• Data Manipulation
• Exploratory Data Analysis
• Data Science Models
• Data Transformation

• Collaboration
• Communication
• Problem Solving
• Stakeholder Engagement
• Translating Technical Concepts

• Data Science Certifications

• Data Science
• Analytical Concentration
• Production Environment
• Technical and Non-Technical Audiences

• Data Visualization Tools