Data Scientist I

Summary

CareSource is seeking a Data Scientist I to support predictive modeling, machine learning, and artificial intelligence initiatives that improve operational, clinical, financial, and marketing processes. The role involves analyzing structured and unstructured data, validating models and outcomes, developing visualizations, collaborating cross-functionally, and preparing end-to-end model pipelines for business use.

Responsibilities

• 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

Skills

• 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
• Familiarity with SQL and at least one of the following programming languages: Python or R
• 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
• Experience with cloud services (such as Azure, AWS or GCP) and modern data stack (such as Databricks or Snowflakes) preferred
• Preferred beginner level of knowledge of developing reports or dashboards in Power BI or other business intelligence applications

Qualifications

Must Haves

• 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
• Familiarity with SQL and at least one of the following programming languages: Python or R
• 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

Nice to Haves

• Experience with cloud services (such as Azure, AWS or GCP) and modern data stack (such as Databricks or Snowflakes) preferred
• Preferred beginner level of knowledge of developing reports or dashboards in Power BI or other business intelligence applications

Benefits

• You may qualify for a bonus tied to company and individual performance.
• A substantial and comprehensive total rewards package.