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Job Summary
The Data Scientist 2 works closely with key business stakeholders to develop use cases related to difficult to solve highly complex business challenges across varied workstreams in different services lines. The Data Scientist 2 creates complex machine learning models used to identify key data features that will enable the models to derive insights that are predictive in nature and enable stakeholders to take action to improve business outcomes. DS2 will own the building/deployment of complex AI Agentic AI Systems for our customer-facing products. The position works closely with junior team members to mentor and guide their work while collaborating with senior team members and data science managers to deliver impactful solutions.
Essential Functions of the Role
Manages project timelines, deliverables, and outcomes, ensuring alignment with organizational goals
Measures and delivers tangible insights and value to improve health system outcomes (improved customer experience, acute clinical, quality, safety, etc.) by leveraging advanced data science and engineering methodologies.
Designs complex machine learning systems using programming skills, which involves assessing and organizing large datasets, executing tests/experiments to automate predictive models.
Collaborates with senior team members and key business stakeholders to define, frame, and scope customer pain points where big data interventions may offer important mitigations and develop robust project plans with key milestones, detailed deliverables, robust work tracking protocols, and risk mitigation strategies.
Works directly with multiple business partners to develop requirements and provide technical solutions across varied workstreams in different service lines.
Iterates and improves the explain-ability, robustness, and scalability of complex ML models.
Manages multiple stakeholder relationships effectively, curating use cases and data features.
Performs other position-appropriate duties as required in a competent, professional, and courteous manner.
Key Success Factors
Master’s degree in a quantitative field like computer science, engineering, statistics, mathematics, economics, or related field or significant, demonstrated experience in the role. PhD preferred.
5+ years of hands-on data scientist mathematical predictive modeling experience in a business environment or equivalent.
Proficiency in common language / tools for AI/ML (e.g. Python/Pyspark, SQL, Pydantic, Langchain etc.).
Experience working in a cloud environment such as Azure, and their ML services and tooling.
Strong interpersonal and communication skills in addition to technical skillset. Ability to build strong relationships, work within and lead teams, and translate technical concepts simply for non-technical stakeholders.
Experience managing multiple complex and scaled data science projects concurrently.
Experience investigating and implementing cutting edge IT technologies and platforms in a large-scale organization.
Advanced knowledge of statistical and machine learning techniques (deep learning, boosted trees, reinforcement learning, etc.).
Technical expertise with multiple compute environments.
Experience working in EDW cloud technologies – e.g. Snowflake and Databricks.
Salary Range
The pay range for this position is $54.88/hour ($114,150/year) for those with entry-level qualifications up to $85.07 ($176,945) for those highly experienced. The specific rate will depend upon the successful candidate’s specific qualifications and prior experience.
Belonging Statement
We believe that all people should feel welcomed, valued and supported.
Qualifications
EDUCATION – Masters’ or Bachelors plus 2 years of work experience above the minimum qualification
EXPERIENCE – 5 Years of Experience
As a health care system committed to improving the health of those we serve, we are asking our employees to model the same behaviours that we promote to our patients. As of January 1, 2012, Baylor Scott & White Health no longer hires individuals who use nicotine products. We are an equal opportunity employer committed to ensuring a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.
