Description:

Qventus is a leader in healthcare transformation, focusing on patient care through innovative solutions that utilize machine learning, generative AI, and behavioral science.
As a Senior Data Scientist / LLM Engineer, you will explore Qventus’ healthcare dataset to develop advanced solutions using various machine learning and statistical methods.
You will evaluate modeling approaches, build features, implement algorithms, and collaborate with product teams to enhance ML & LLM solutions.
The role involves solving operational challenges in healthcare by developing and tuning impactful models.
You will collaborate with Product and Clinical partners to deploy proof of concept solutions in strategic business areas.
Designing experiments and analytics to measure the impact of interventions in healthcare settings is a key responsibility.
You will create tools to improve transparency in Data Science architecture and foster collaboration with engineering and analytics teams.

Requirements:

You must have 3+ years of research experience with a variety of statistical and machine learning techniques, especially in NLP and explainable ML using Python.
A minimum of 2 years of industry experience in developing, launching, and maintaining machine learning systems at scale is required.
You should have at least 1 year of experience in developing and tuning LLM systems, with strong experience in RAG preferred.
Strong cross-functional communication skills with both technical and non-technical partners are essential.
Hands-on data engineering experience, including data manipulation, cleaning, and pipeline creation using SQL and Python, is necessary.
A strong foundation in software development, with a focus on high code quality and maintainability, is required.

The salary range for this position is $150,000 to $180,000, based on various factors including location and experience.
Qventus offers Open Paid Time Off, paid parental leave, and professional development opportunities.
Additional benefits include wellness and technology stipends, a generous employee referral bonus, and employee stock option awards.
The company is committed to diversity, equity, inclusion, and belonging, ensuring fair hiring processes and meaningful roles for underrepresented groups.