Job Description
We’re looking for the optimists, the changemakers, the status quo smashers, and those who reject the very idea of the impossible. At Clarify, we firmly believe that healthcare can (and should) perform better. Our AI-driven healthcare analytics solutions help some of the biggest entities in healthcare pinpoint new ways to do so, starting with their margins and their missions. We’re looking for talented individuals to join us in blueprinting healthcare’s next evolution.
Clarify is looking for Senior Data Science Engineer to focus on machine learning (ML) engineering and operations (MLOps).
Does this sound like you?
·You have an enthusiastic, energetic personality and an inquiring, investigative mind.
·You enjoy finding patterns to automate or simplify work.
·You value working with hardworking, curious, and supportive teammates.
·You embrace change as an opportunity to learn.
·You believe diversity of thought improves our outcomes.
·You have a desire to build technologies that will shape the future.
·You take great care in the details.
The role
- Developing and deploying machine learning (ML) models on large healthcare datasets; proficient in fostering a project through the entire model development lifecycle, including MLOps
- Designing rigorous experiments that incorporate different modeling techniques, feature engineering, and feature selection to optimize model performance, interpretability, and identify actionable insights
- Drive innovation by staying current with cutting-edge research in machine learning, AI, GenAI, LLMs, and related fields, and translating insights into scalable, impactful solutions
- Collaborating with our product management, engineering, clinical, and customer success to provide a data-driven perspective on business problems
- Translating business problems and sometimes complex statistical approaches into actions, balancing creativity with engineering practicality
What we are looking for
- Demonstrable experience in applied machine learning and writing production-level code in the healthcare industry (e.g., biostatistics, health economics, epidemiology, genomics, etc.)
- Resourcefulness in a variety of machine learning packages in Python, with a keen knowledge of optimal selections concerning predictive performance, computation time, and model interpretability
- Self-sufficiency in researching new features and building resources necessary where they do not already exist
- Practicality and systematic problem-solving skills necessary to find elegant solutions to complex problems
- Thrive in a fast-paced environment and capable of managing multiple projects effectively
- An ownership mindset and desire to be the technical expert in the room
- 7+ years of direct data science experience or 5+ years of direct data science experience with a graduate degree in a technical discipline (e.g., computer science, data science, statistics, bioengineering, biostatistics, etc.)
- Proficiency in Python and SQL
- Experience with Machine Learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
Bonus points for
- Familiarity with AWS, Spark, Bash/Unix , Git.
- Exposure to Generative AI technologies and tools
What we offer you
- Competitive compensation (base + bonus)
- Quality health insurance
- Traditional 401K plan
- Vision, dental, disability and life insurance
- Flexible Spending Accounts and Commuter Benefits
- Generous PTO
- Flexibility
- Monthly wellness stipend
- Remote friendly
- A collaborative workplace, which will challenge you and celebrate your work
- A chance to learn with and from interesting and enthusiastic colleagues
$168,500 - $198,000 a year
Don’t meet every single requirement? At Clarify we are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles!
We believe that a happy, diverse, and impact-driven team is critical to our mission of transforming healthcare. Having a diverse team allows us to bring more ideas to the table when working on lighting the path to higher-value care. We embrace employees and applicants of all backgrounds, including those of traditionally underrepresented groups. With this in mind, we do not discriminate against any employee or applicant because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, the basis of disability, homelessness, reproductive health decisions or any other federal, state or local protected class.
