Job Description
We are seeking an experienced Senior Data Scientist with a strong background in healthcare analytics, statistical modeling, and machine learning. In this role, you will work on complex datasets from diverse healthcare sources to develop predictive models, perform advanced statistical analysis, and extract actionable insights. You will play a key role in building data-driven solutions that improve patient outcomes, optimize clinical workflows, and enable next-generation AI-powered healthcare applications.
Advanced Statistical Modeling: Apply rigorous statistical techniques (regression, hypothesis testing, survival analysis) to healthcare data for predictive and prescriptive analytics.
Time Series Analysis: Develop models for forecasting and anomaly detection in longitudinal healthcare data (e.g., patient vitals, treatment timelines).
Feature Engineering: Design and implement robust feature extraction and transformation pipelines for structured and unstructured healthcare data.
Large-Scale Data Handling: Work with high-volume datasets from EHRs, claims, and sensor data using distributed computing frameworks (Spark, Dask).
Predictive Modeling: Build and validate machine learning models for risk stratification, disease progression, and patient engagement.
Data Quality & Governance: Ensure compliance with healthcare data standards (HIPAA, HL7, FHIR) and maintain data integrity.
Visualization & Communication: Create compelling dashboards and visualizations to communicate insights to clinicians and business stakeholders.
Collaboration: Partner with product managers, engineers, and clinical experts to translate business needs into data-driven solutions.
Required Qualifications
Education: Master’s or Ph.D. in Statistics, Data Science, Computer Science, or related field.
Experience: 5+ years in data science roles, with at least 2 years in healthcare analytics.
Statistical Expertise: Strong knowledge of regression models, Bayesian methods, and hypothesis testing.
Time Series & Forecasting: Hands-on experience with ARIMA, Prophet, or deep learning-based time series models.
Programming Skills: Proficiency in Python (pandas, NumPy, scikit-learn), SQL, and experience with PostgreSQL or similar databases.
Big Data Tools: Experience with Spark, Hadoop, or cloud-based data platforms (AWS, Azure, GCP).
Feature Engineering: Proven ability to design features for complex healthcare datasets.
Domain Knowledge: Familiarity with clinical terminologies, EHR systems, and healthcare workflows.
While we've outlined some key qualities we typically seek, it's essential to remember that there might be additional unique strengths and talents you possess that would make you an exceptional match for us, even if they're not explicitly mentioned. Studies have consistently highlighted the significance of this principle, particularly for individuals from disenfranchised backgrounds, including women and other marginalized groups. These individuals often hesitate to apply unless they meet every single requirement, unlike their male counterparts who are more inclined to apply when they meet around 60% of the criteria.
The message we want to convey is that taking a leap of faith and applying can be incredibly rewarding. Your distinct abilities and perspectives could be exactly what we need to create a more diverse and inclusive team. So, don't hesitate—apply today and let's explore the exciting possibilities together!
All your information will be kept confidential according to EEO guidelines.
