The Data Scientist I is responsible for supporting the design and validation of predictive models, machine learning models, and artificial intelligence that inform and improve business processes across the organization (operational, clinical, financial, marketing, etc.).
Essential Functions:
- Support the creation, maintenance, and communication of an analytical plan for data science projects
- Assist in mining and analyzing large structured and unstructured datasets
- Employ wide range of data sources to develop algorithms for predicting risk and understanding drivers, detecting outliers, etc
- Support the development of visualizations that demonstrate the efficacy of developed algorithms
- Contribute to statistical validation and analysis of outcomes associated with clinical programs and interventions under guidance
- Collaborate with other teams to integrate with existing solutions
- Communicate results and ideas to key stakeholders
- Assist in preparing code for operationalization of end-to-end model pipeline and deliverable for business consumption
- Researching and staying up-to-date on emerging technologies
- Perform any other job related duties as requested.
Education and Experience:
- Bachelor's degree in data science, mathematics, statistics, engineering, computer science, other related field required
- Equivalent years of relevant work experience may be accepted in lieu of required education
- Experience with cloud services (such as Azure, AWS or GCP) and modern data stack (such as Databricks or Snowflakes) preferred
- Familiarity with SQL and at least one of the following programming languages: Python or R
- Preferred beginner level of knowledge of developing reports or dashboards in Power BI or other business intelligence applications
- Ability to understand basic statistical analyses and techniques including A/B testing, general significance testing, and sampling methodologies
- Working knowledge of predictive modeling and machine learning algorithms such as generalized linear models, non-linear supervised learning models, clustering, decision trees, and dimensionality reduction
- Working knowledge of unsupervised and deep leaning methodologies such as clustering, neural networks, and transformers
- Working knowledge of natural language processing technologies such as optical character recognition, named entity recognition, visual learning models, and large language models
- Working knowledge in NLP-specific feature extraction techniques such as tokenization, embeddings, and text-based transformations
- Familiarity in feature engineering techniques and exploratory data analysis
- Familiarity with optimization techniques and artificial intelligence methods
- Ability to mine and analyze large quantities of structured and unstructured data and identify patterns, irregularities, and deficiencies
- Proficient with MS office (Excel, PowerPoint, Word, Access)
- Demonstrated critical thinking, verbal communication, presentation and written communication skills
- Ability to work independently and within a cross-functional team environment
- None required
- General office environment; may be required to sit or stand for extended periods of time
- Travel is not typically required
Compensation Range:
$72,200.00 - $115,500.00CareSource takes into consideration a combination of a candidate’s education, training, and experience as well as the position’s scope and complexity, the discretion and latitude required for the role, and other external and internal data when establishing a salary level. In addition to base compensation, you may qualify for a bonus tied to company and individual performance. We are highly invested in every employee’s total well-being and offer a substantial and comprehensive total rewards package.
Compensation Type (hourly/salary):
SalaryOrganization Level Competencies
Fostering a Collaborative Workplace Culture
Cultivate Partnerships
Develop Self and Others
Drive Execution
Influence Others
Pursue Personal Excellence
Understand the Business
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