Digital Customer Engagement AI Data Scientist
Role summary
Seeking an AI Data Scientist specializing in Digital Customer Engagement within the healthcare sector. This role involves designing and deploying machine learning, deep learning, and generative AI models to enhance patient and stakeholder interactions. Responsibilities include building end-to-end data science pipelines, implementing MLOps practices, and ensuring responsible AI adoption. The position requires strong Python, SQL, and ML algorithm experience, with familiarity in cloud platforms and MLOps frameworks. Experience in regulated healthcare environments and with GenAI/LLM applications is a plus. The role emphasizes collaboration with cross-functional teams to deliver scalable AI products that improve customer experiences and healthcare outcomes.
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Digital Customer Engagement AI Data Scientist in the United States.
This role sits at the intersection of advanced AI, customer engagement, and healthcare innovation, where data-driven insights directly influence how organizations interact with patients and stakeholders. You will design and deploy machine learning solutions that power digital engagement strategies, improving personalization, efficiency, and decision-making across global healthcare operations. Working in a highly collaborative, research-driven environment, you will transform complex structured and unstructured data into scalable AI products. The position combines hands-on model development with strategic input into responsible AI adoption and enterprise data architecture. You will partner closely with cross-functional teams including engineering, product, and business leaders to bring AI solutions into production. Your work will have a tangible impact on improving customer experiences while supporting safer, more effective healthcare outcomes at scale.
Accountabilities
- Develop and deploy machine learning, deep learning, and generative AI models to enhance digital customer engagement and solve real-world business challenges, including predictive and prescriptive use cases.
- Build and maintain end-to-end data science pipelines, covering data ingestion, feature engineering, model training, evaluation, and continuous improvement.
- Implement and manage MLOps practices such as model monitoring, versioning, drift detection, retraining, and production optimization.
- Collaborate with data engineering teams to ensure robust, scalable, and governed data foundations for AI solutions.
- Translate business and customer engagement needs into data science problems with measurable success criteria and actionable insights.
- Communicate analytical findings clearly to technical and non-technical stakeholders, supporting adoption and value realization across the organization.
- Ensure responsible AI practices, including compliance with governance frameworks, data privacy requirements, and ethical AI principles.
Requirements
- Advanced degree (Master’s or PhD preferred) in Data Science, Computer Science, Statistics, Mathematics, AI, or a related field.
- Strong hands-on experience with Python and data science libraries such as pandas, NumPy, scikit-learn, TensorFlow, or PyTorch.
- Solid understanding of machine learning algorithms, statistical modeling, and model evaluation techniques.
- Experience working with SQL and large-scale datasets in complex data environments.
- Proven ability to deploy and operationalize AI/ML models in production or near-production environments.
- Familiarity with cloud-based AI platforms (e.g., Azure ML, Databricks, Snowflake) and modern MLOps frameworks.
- Strong communication skills, with the ability to bridge technical and business perspectives effectively.
- Experience in regulated environments (e.g., healthcare) and exposure to GenAI/LLM applications is a strong plus.
Benefits
- Competitive base salary with additional eligibility for variable compensation depending on role structure and performance
- Comprehensive medical, dental, and vision insurance coverage
- 401(k) retirement savings plan with employer support
- Paid time off, sick leave, and flexible work arrangements
- Life insurance, short-term and long-term disability coverage
- Opportunities for professional development and career progression into senior AI and leadership roles
- Inclusive, global, and innovation-driven work environment focused on impactful healthcare solutions
How Jobgether Works
We use an
AI-powered matching process
to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice:
By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
