Data Scientist I
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Role details
Tech stack
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Job description
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.)., * 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.
Requirements
- 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
Competencies, Knowledge and Skills:
- 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
Benefits & conditions
- 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 - $115,500.00
CareSource 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):
Salary
Organization 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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