Senior Data Scientist, Healthcare AI & Analytics

Teladoc Health; United States; On-site; USD 200,000 - 215,000; Full time

Job summary

Teladoc Health is seeking a Staff Data Scientist in the United States to lead complex data science initiatives and develop analytics and algorithmic solutions that address high-impact healthcare problems.

You will apply advanced techniques, mentor fellow data scientists, and collaborate with engineering, product, and clinical teams to translate challenging problems into scalable ML solutions. Travel up to 10% may be required as needed.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Business Management, or a related field.
• 8+ years of experience applying machine learning, statistics, and quantitative methods to solve complex business or healthcare problems.
• Strong experience with data processing and analysis using SQL and distributed data-processing technologies such as Spark.
• Strong programming skills in Python, Scala, R, or equivalent languages used for data science and machine learning.
• Experience designing, developing, evaluating, and communicating machine learning or statistical solutions.
• Demonstrated ability to independently lead complex analytical projects involving multiple stakeholders.
• Strong understanding of machine learning, statistical inference, experimentation, and analytical methodology.
• Ability to communicate technical concepts, results, limitations, and recommendations effectively to technical and non-technical audiences.
• Experience mentoring or providing technical guidance to other data scientists.
• Advanced degree in a STEM field or equivalent experience and expertise.
• Travel: Up to 10%, subject to business needs.

Responsibilities

• Lead complex data science, machine learning and AI initiatives of significant scope, operating with a high degree of independence.
• Design, develop, and maintain analytics pipelines and algorithmic data products that address complex healthcare and business problems.
• Apply advanced analytical methods, including supervised and unsupervised learning, statistical inference, causal modeling, and other quantitative techniques, to generate actionable insights.
• Translate ambiguous business, clinical, and product problems into clearly defined analytical and machine learning approaches.
• Provide technical leadership throughout the lifecycle of data science initiatives, from problem formulation through model development and deployment.
• Establish and promote data science best practices, including reproducible analysis, experiment design, version control, peer review, documentation, and sound model development practices.
• Serve as a technical resource for other data scientists through mentorship, coaching, design guidance, and code and model reviews.
• Partner with Data Eng, ML Eng, Product, Clinical, and business stakeholders to ensure analytical solutions address business needs.
• Communicate complex analyses, methodologies, trade-offs, results, and recommendations clearly to technical and non-technical audiences.
• Develop influential presentations and recommendations that enable stakeholders to make data-informed decisions.
• Identify opportunities to improve analytical approaches, reusable methodologies, tools, and data science capabilities.
• Manage multiple complex initiatives while keeping stakeholders informed of progress, risks, dependencies, and outcomes.
• Contribute to technical standards and improve the quality and reproducibility of data science work across the broader team.

Skills

Machine learning

Statistics

Data analysis

Mentorship

Communication

Education

Bachelor's degree in CS/Engineering/related

Advanced degree in STEM

Tools

SQL

Spark

Python

Scala

R

Job description

Teladoc Health is seeking a Staff Data Scientist in the United States to lead complex data science initiatives and develop analytics and algorithmic solutions that address high-impact healthcare problems.

You will apply advanced techniques, mentor fellow data scientists, and collaborate with engineering, product, and clinical teams to translate challenging problems into scalable ML solutions. Travel up to 10% may be required as needed.