Senior Data Science Engineer (Remote - US) - job 1 of 2

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Data Science Engineer in the United States.

As a Senior Data Science Engineer, you will design, develop, and deploy machine learning models on large-scale healthcare datasets, contributing to solutions that drive meaningful improvements in patient care and operational efficiency. This role spans the full ML lifecycle, from feature engineering and modeling to MLOps and production deployment. You will collaborate closely with cross-functional teams—including product management, engineering, and clinical experts—to translate complex data into actionable insights. Innovation, rigor, and technical excellence are key, as you integrate cutting-edge AI, generative AI, and ML research into practical, scalable solutions. You will also serve as a technical mentor, guiding peers and shaping best practices across the data science organization. This role offers the opportunity to make a measurable impact in a mission-driven, fast-paced environment where creativity and precision are highly valued.

Accountabilities

• Develop and deploy machine learning models on healthcare and other large-scale datasets.
• Design and implement experiments involving feature engineering, selection, and various modeling techniques to optimize predictive performance and interpretability.
• Integrate models into production systems following MLOps best practices for scalability, reproducibility, and monitoring.
• Collaborate with product, engineering, clinical, and customer success teams to address complex business problems with data-driven solutions.
• Translate statistical and machine learning approaches into actionable insights, balancing creativity with engineering feasibility.
• Stay current with AI/ML research, including generative AI and large language models, applying innovations to practical solutions.
• Provide technical leadership and mentorship within the data science team.

• 7+ years of professional data science experience, or 5+ years with a graduate degree in computer science, data science, statistics, bioengineering, or a related technical field.
• Strong proficiency in Python and SQL, with experience in machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch.
• Demonstrable experience in applied machine learning, including production-level code, preferably in healthcare or related domains (e.g., biostatistics, genomics, health economics, epidemiology).
• Solid understanding of feature engineering, model evaluation, interpretability, and MLOps principles.
• Strong problem-solving, systematic thinking, and self-sufficiency in building resources and features as needed.
• Ability to manage multiple projects in a fast-paced, dynamic environment.
• Excellent collaboration skills and an ownership mindset; eager to be a technical expert and mentor.
• Bonus points: experience with AWS, Spark, Bash/Unix, Git, and exposure to generative AI tools.

• Competitive base salary plus bonus potential ($168,500 - $198,000/year).
• Comprehensive health insurance (medical, dental, vision) including dependents.
• Traditional 401(k) plan with company contribution.
• Flexible spending accounts and commuter benefits.
• Paid time off and generous parental leave.
• Remote-friendly work environment with flexible scheduling.
• Monthly wellness stipend and other perks to support personal well-being.
• Collaborative, mission-driven culture focused on learning and professional growth.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role.
Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

#LI-CL1