Alignment Healthcare is a data and technology driven healthcare company focused partnering with health systems, health plans and provider groups to provide care delivery that is preventive, convenient, coordinated, and that results in improved clinical outcomes for seniors. We are experiencing rapid growth (backed by top private equity firms), our Data Science team is looking for the best and brightest data scientists. Data drives the way we make decisions. We love our customers and understanding them better makes it possible to provide the best clinical outcome and care experience. This position will play a key role in uncovering deep insights from data using advanced machine learning technologies and advanced statistical analysis, processing very large data sets using cloud-based data pipelines, variety of analytic tools, visualizations and delivering actionable healthcare insights & solutions.
General Duties/Responsibilities (May include but are not limited to):
Collaborate with key business leaders to understand their business problems and come up with analytical solutions.
Applying coding skills and knowledge data structures to develop projects in partnership with other scientists and engineers in the team
Build end-to-end data science solutions which will improve healthcare outcomes and reduce the cost for our members.
Build customer segmentation models to better understand our customers, and tailor the clinical outcome and healthcare care experience for them.
Develop scalable and efficient modeling algorithms that can work in production systems.
Collaborate with the engineering team to build end-to-end cloud based machine learning production pipelines.
Design and implement online experiments and experimental frameworks
Contribute to the integration of large language models (LLMs) into data science solutions to enhance natural language understanding, data retrieval, and predictive analytics capabilities.
Minimum Requirements:
2+ years of relevant experience in predictive modeling and analysis
Education/Licensure:
PhD in Computer Science, Engineering, Mathematics, Statistics, or related field
Other:
Excellent communication, analytical and collaborative problem-solving skills
Experience in building end to end data science solutions and applying machine learning methods to real world problems with measurable outcomes.
Deep understanding and experience with various machine learning algorithms, including deep neural networks, natural language processing, kernel methods, dimensionality reduction, ensemble methods, HMM and graph algorithms.
Solid data structures & algorithms background.
Strong programming skills in one of the following: Python, Java, R, Scala or C++
Demonstrated proficiency in SQL and relational databases.
Experience with data visualization and presentation, turning complex analysis into insight.
Experience in setting experimental analytics frameworks or strategies for complex scenarios.
Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development, and evaluation data sets, etc.
Experience with manipulating and analyzing complex, high-volume, high-dimensionality and unstructured data from varying sources
Preferred Qualifications:
Healthcare experience
Experience in Big Data processing technologies: Hadoop, Spark, Cosmos
Experience in Azure, AWS or other cloud ecosystems.
Experience in NoSQL databases.
Published work in academic conferences or industry circles.
Demonstrable track record dealing well with ambiguity, prioritizing needs, and delivering results in an agile, dynamic startup environment
Experience with fraud detection in medical claims, including methods like anomaly detection, predictive modeling, and data pattern recognition to identify fraudulent activities.
Work Environment:
The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.