Data Scientist

Job Description

Our client is seeking a Data Scientist for an exciting contract to hire scenario. The Data Scientist helps drive data-informed decision-making in behavioral health care. This position will leverage advanced analytics to improve our services and patient outcomes. This role involves extracting, analyzing, and interpreting large amounts of data to identify patterns, trends, and insights that can help our organization make data-driven decisions.

Duties
• Collaborate with clinical, product design, and engineering teams to understand and address their data needs.
• Research and develop innovative statistical models for behavioral health data analysis.
• Communicate findings effectively to stakeholders, including clinicians and executives.
• Enable smarter business processes by using analytics for meaningful insights.
• Stay current with technical and industry developments in behavioral health and data science.
• Oversee the design and delivery of reports and dashboards to internal teams and key stakeholders.
• Collect, clean, and organize large datasets from various sources, ensuring data quality and compliance with healthcare regulations.
• Validate data for uniformity and accuracy.
• Use statistical and machine learning techniques to analyze data and develop predictive models for patient outcomes and resource allocation.
• Collaborate with cross-functional teams to implement data-driven solutions that enhance patient care and operational efficiency.
• Continuously monitor and evaluate the performance of predictive models and make necessary improvements.
• Serve as lead data strategist to identify and integrate new datasets that can be leveraged through our product capabilities, working closely with the engineering team to develop data products.
• Execute analytical experiments to help solve problems across various domains and industries within behavioral health.
• Identify relevant data sources and sets to mine for client business needs and collect large structured and unstructured datasets and variables.
• Devise and utilize algorithms and models to mine big-data stores; perform data and error analysis to improve models; clean and validate data for uniformity and accuracy.
• Analyze data for trends and patterns and interpret data with clear objectives.
• Implement analytical models in production by collaborating with software developers and machine-learning engineers.
• Oversee the design and delivery of reports and dashboards to internal teams and key stakeholders.
• Collect, clean, and organize large datasets from various sources.
• Implement analytical models by collaborating with analysts and developers.
• Validate data for uniformity and accuracy.
• Use statistical and machine learning techniques to analyze data and develop predictive models.
• Communicate insights and findings to stakeholders in a clear and concise manner.
• Collaborate with cross-functional teams to implement data-driven solutions.
• Continuously monitor and evaluate the performance of predictive models and make necessary improvements.
• The environment at is fluid and roles and responsibilities may be altered to accommodate changing business conditions and objectives. Employees may be asked to perform duties that are outside specific work that is listed within their job descriptions. This position may require you to work standard hours, as well as flexible hours both before and after standard hours necessary to positions needs.

Requirements
• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field.
• 5+ years of experience in data science, preferably in healthcare or nonprofit sectors.
• Knowledge of HIPAA and other healthcare data regulations preferred.
• Strong analytical and problem-solving skills.
• Proficiency in programming languages such as Python or R.
• Experience with data visualization tools and techniques, such as Power BI.
• Excellent communication and collaboration skills.
• Knowledge of data structures, algorithms, and software engineering principles.
• Experience with various data sources, formats, and platforms, such as SQL, NoSQL, Hadoop, Spark, or Azure.
• Ability to perform data preprocessing, cleansing, exploration, and analysis using statistical and machine learning techniques.
• Experience building, testing, and deploying predictive, prescriptive, and descriptive models using supervised and unsupervised learning methods.
• Experience utilizing visualization tools to communicate the results and implications of data analysis.
• Demonstrated experience applying data science methods to real-world data problems.
• Excellent communication and presentation skills, both verbal and written, to convey complex findings and insights to technical and non-technical audiences.
• Curiosity, creativity, and passion for solving data-driven problems and delivering business value.

Job Requirements

On-Site