Keylent Inc
Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist with a focus on healthcare, requiring a minimum of five years' experience in data science, statistical analysis, and machine learning. The contract length is "unknown," with a pay rate of "unknown." Remote work is available.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
February 21, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Unknown
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Sacramento, CA
-
🧠 - Skills detailed
#Programming #R #Informatica BDM (Big Data Management) #Datasets #Visualization #Scala #Data Analysis #Data Management #Scripting #Python #Data Mining #Data Science #BI (Business Intelligence) #SQL (Structured Query Language) #Data Manipulation #Leadership #Big Data #ML (Machine Learning) #"ETL (Extract #Transform #Load)" #A/B Testing #Statistics #Data Engineering
Role description
Healthcare experience with State or Federal is very desirable
Senior Data Scientist – Responsibilities
• Analyze, process, and model data.
• Communicate results to inform actionable plans and organizational decisions.
• Exercise judgment in selecting appropriate analytical methods based on the question and supporting data.
• Translate analytical methods and findings for a lay audience.
• Understand dataset constraints and identify relevant data sources.
• Be fluent in one or more data manipulation programming languages (e.g., R, Python, Scala, etc.).
• Work with structured and unstructured datasets of varying sizes and complexity.
• Have experience in big data management and data mining.
• Organize, clean, and transform data into usable formats.
• Apply appropriate statistical models or algorithms.
• Automate data collection and preprocessing.
• Perform analysis, including ad-hoc analysis.
• Identify trends and patterns across large and multiple datasets.
• Answer specific analytical questions.
• Develop and validate hypotheses.
• Conduct exploratory data analysis (EDA).
• Create visualizations and charts to:
• Understand and communicate insights.
• Identify underlying data issues (e.g., missing data, poor quality).
• Present findings to key stakeholders.
• Demonstrate relevant domain knowledge.
• Develop, test, and implement predictive and machine-learning models.
• Use a mix of statistical and machine learning approaches.
• Manage and mentor junior data scientists.
• Provide leadership in introducing new methods and supporting infrastructure.
• Collaborate with:
• Data engineers
• Data modelers
• Business intelligence analysts
• IT staff
• Support setup of complex ongoing analyses feeding dashboards or other data products.
Experience Requirements
• Minimum of five (5) years of relevant experience in:
• Mathematical modeling
• Statistical analysis
• Machine learning
• A/B testing
• Data science in an applied context
• Experience using:
• Statistical programming languages
• SQL
• Other scripting and statistical tools
• Proficiency in one or more visualization tools.
Education Requirements
• Master’s degree or higher in:
• Economics
• Statistics
• Math
• Engineering
• Science
• Social science
• Data science
• Other quantitative-focused field
• OR additional two (2) years of qualifying experience may substitute for required education,
• Along with demonstrated completion of training, bootcamps, or supplemental coursework in:
• Mathematical modeling
• Statistical analysis
• Machine learning methods
Healthcare experience with State or Federal is very desirable
Senior Data Scientist – Responsibilities
• Analyze, process, and model data.
• Communicate results to inform actionable plans and organizational decisions.
• Exercise judgment in selecting appropriate analytical methods based on the question and supporting data.
• Translate analytical methods and findings for a lay audience.
• Understand dataset constraints and identify relevant data sources.
• Be fluent in one or more data manipulation programming languages (e.g., R, Python, Scala, etc.).
• Work with structured and unstructured datasets of varying sizes and complexity.
• Have experience in big data management and data mining.
• Organize, clean, and transform data into usable formats.
• Apply appropriate statistical models or algorithms.
• Automate data collection and preprocessing.
• Perform analysis, including ad-hoc analysis.
• Identify trends and patterns across large and multiple datasets.
• Answer specific analytical questions.
• Develop and validate hypotheses.
• Conduct exploratory data analysis (EDA).
• Create visualizations and charts to:
• Understand and communicate insights.
• Identify underlying data issues (e.g., missing data, poor quality).
• Present findings to key stakeholders.
• Demonstrate relevant domain knowledge.
• Develop, test, and implement predictive and machine-learning models.
• Use a mix of statistical and machine learning approaches.
• Manage and mentor junior data scientists.
• Provide leadership in introducing new methods and supporting infrastructure.
• Collaborate with:
• Data engineers
• Data modelers
• Business intelligence analysts
• IT staff
• Support setup of complex ongoing analyses feeding dashboards or other data products.
Experience Requirements
• Minimum of five (5) years of relevant experience in:
• Mathematical modeling
• Statistical analysis
• Machine learning
• A/B testing
• Data science in an applied context
• Experience using:
• Statistical programming languages
• SQL
• Other scripting and statistical tools
• Proficiency in one or more visualization tools.
Education Requirements
• Master’s degree or higher in:
• Economics
• Statistics
• Math
• Engineering
• Science
• Social science
• Data science
• Other quantitative-focused field
• OR additional two (2) years of qualifying experience may substitute for required education,
• Along with demonstrated completion of training, bootcamps, or supplemental coursework in:
• Mathematical modeling
• Statistical analysis
• Machine learning methods
