Yang Yang Email & Phone Number

Kirkland, Wa, Us

San Francisco, Ca, Us

Orange, Ca, Us

Lead Clinical Analytics AI research, deployment and reporting. - Admission Risk Model and CareAnyWhere program help Alignment achieve a 38% reduction in admissions per thousand members as compared to Medicare Fee-For-Service operated in the same market. This led to more than 150M in annual savings and greatly improved members' health condition.- Lead Smart Market Expansion project using SDOH data and ML models. The innovation helped 2024 AEP achieve a 50.5% YOY member growth rate. By the end of 2024 Q1, Alignment serves 160,000+ members.- Lead Drug Safety project using RWE and NLP techniques.- Lead Member Experience Understanding and Improvement project using NLP techniques.- Lead POC projects and manage collaborative relationships with top-notch platforms like Databricks and JohnSnowLabs.- Support a few other projects including care management program ROI report, Star rating improvement, etc.Recruit, manage and mentor data scientists; plan the strategic initiative roadmap for the Data Science department; govern the tech stack and platforms for the Data Science department; lead the publication and conference presentation.

Somerville, Massachusetts, Us

Find out What Works for Whom. Represent GNS Healthcare in Seattle/Portland to work with Cambia Health Solutions and Regence BlueCross BlueShield (GNS’ lead investor and strategic partner) as an embedded employee. Focus: Causal Trajectory for High Impact Conditions. Identification of early inflection point and cost saving opportunities in Complex Patients (with multiple chronical conditions) and follow-up intervention optimization.Role: Propose and lead the project. Arrange internal resources, align value with client, technical oversight, ETL and analytic conceptualization and implementation, business intelligence investigation, report and presentation both internally and to client. My another work at GNS was with Cigna Insurance as the client and the stakeholder. As one of the two data scientists in a team of 8 people including BD and PM, we worked on the care management intervention optimization project for Cigna's multi-markets multi-programs of care management, including oncology, pregnant women and baby, chronic disease, catastrophic, etc. We delivered the solution within 5 months and this delivery successfully secured GNS the Series D fund led by Cigna Ventures at 23 Million (https://www.forbes.com/sites/brucejapsen/2019/07/09/cigna-invests-in-gns-healthcares-precision-medicine-venture).

Brentford, Middlesex, Gb

Utilize Data Science to understand human genome regulatory profile and locate drug target.Projects: 1, Investigate the sequencing experiment conditions' effects on the sequencing result (DNA fragments reads) quality. A better controlled sequencing experiment achieves increased efficiency and further reduces the cost. 2, Machine learning application development based on the DNA sequencing machine log file. Techniques include text parsing, ETL, feature engineering, machine learning application and result visualization.

Amsterdam, Noord-Holland, Nl

Responsibilities:Heathcare Big Data Analytics and Machine Learning;Pipeline Development;R on Hadoop, Spark and HPC;Collaboration with Business Consultants;Spotlight:1, Smart hospital network project. Stakeholders: Business consultants, regional hospitals, data science team.Methods: Panel discussion with stakeholders, Data integration of CMS claim data, SQL query, statistics aggregation, tableau visualization and statistical modeling. Business insight: optimize regional Accountable Care Organazation (ACO)'s financial performance and primary care quality by helping them identify and engage those Primary Care Physicians, who induced excessive avoidable costs and patient leakage to out-of-network facility/specialist; identify those severe patients for care management to reduce their future avoidable cost and leakage.2, Data integration of de-identified healthcare databases and patient expenditure analysis.Content:Data integration of hospital inpatient data sets, e.g., combined information from clinical, administrative and billing sources. Investigation of the factors associated with/helping predict the patient in-hospital total expenditure, death event and length of stay. I compared the results from multiple ML/statistical algorithms (Linear Model with stepwise model selection by AIC criterion, Elastic Net regularized linear regression, Group based MCP regularized linear regression, Random Forest and Quantile Regression.). I observed some caveats of the data set (e.g., multicollinearity among several explanatory variables, heterogeneous variance of residuals and non-linear effect between some explanatory variables and the response variable - total charges) and proposed a few alternative models robust to these caveats. I verified pros and cons of currently executed algorithms for this data set. I interpreted the outputs, draw statistical inferences and have a discussion of variables' importance to predicting total expenditure and other response variables.

Houston, Texas, Us

(During 06/2014 ~ 06/2015, part time unpaid at this position for paper submission/revision, full-time as a Data Scientist at Philips above.)(During 09/2012 ~ 05/2014, primary responsibility as a Research Bioinformatician at MDACC below, with part time unpaid at this position for previous projects' paper submission/revision.)Statistical methods in identifying association between longitudinal/multivariate traits and common/rare variantsGene-based/region-based association testing methodsPathway-based association testing methodsLongitudinal eQTL GWAS on Systemic SclerodermaNon-parametric functional data analysis in GWAS.Use R, Bash Script, C, SQL languages, and parallel computing platforms such as PBS in school cluster and SGE/SLURM in Texas Advanced Computing Center (TACC).

Houston, Texas, Us

Assist teaching "Biomedical Statistics" as a required course provided in Graduate School of Biomedical Sciences

Houston, Texas, Us

Assist teaching "Intermediate Biostatistics", "Foundation of Biostatistics" and "Theory II of Biostatistics" provided in School of Public Health.

Houston, Texas, Us

Conduct data integration, data manipulation and statistical analysis on lung cancer epidemiological genetics data.

Houston, Tx, Us

Network Biology on Pan-cancerComputational Cancer GenomicsCancer survival prognostic signature identificationHelp with other projects such as pseudogene clinical properties, RNA editting clinical properties (biostatistics & Bioinformatics computational service)Use R, Bash Script, C, SQL languages, and parallel computing platforms such as PBS in department cluster and SGE/SLURM in Texas Advanced Computing Center (TACC).

Indianapolis, In, Us

Under the guidance of Dr. Yunlong Liu on NG-seq data analysis using bioinformatics methods. Topics relate functional genomics especially in breast cancer tissue.

Participate research in various fields under Bioinformatics realm, e.g. Protein structure folding predicition, Biological data pathway analysis, etc.

Professional Education, Data Science

Professional Education, Data Science

Ph.D, Biostatistics And Data Science

M.S, Bioinformatics

Bachelor'S Degree, Biology/Biological Sciences, General