Professional Experience

• Data Science Manager - Customer Analytics Bayer Crop Science (July 2021 - Present)
  • Responsible for creating and implmenting global customer analytics strategies for Bayer crop science’s commercial operations, including identifying and articulating value of analytics solutions with global impact on marketing, customer experience and product offering in NA, EMEA and LATAM.
  • Worked closely with regional and global leaders to define and implement data quality standards to enable development of sustainable and high quality analytics solutions.
  • Developed talent for a high-performing global data science team with members from NA, EMEA and LATAM.
  • Led engagements with external collaborators and vendors to develop capabilities that result in new value streams for BCS commercial.

• Data Sciencee Technical Lead, Bayer Crop Science (Nov 2019 - July 2021)

  • Lead an analytics work stream to support data-driven decisions, such as yield forecasting, growth stage modeling and planting and harvest optimization models, to improve supply chain efficiency and sustainability for Bayer Crop Science’s row crop manufacturing.
  • Serves as a technical manager for a team of data scientists, with responsibilities in mapping technical skills of a team to the actual tasks, as well as workflow management, resource planning, and building our team’s project portfolio.
  • Lead an analytics work stream to support data-driven decisions, such as yield forecasting, growth stage modeling and planting and harvest optimization models, to improve supply chain efficiency and sustainability for Bayer Crop Science’s row crop manufacturing.
  • Serves as a technical manager for a team of data scientists, with responsibilities in mapping technical skills of a team to the actual tasks, as well as workflow management, resource planning, and building our team’s project portfolio.
  • Partner with a global team of domain experts and business leaders to define the content and roadmap of analytics strategy, and serve as a liaison between technical teams and business leaders to translate the value of analytics models and identify business use cases.
  • Provide technical leadership and supervision for a team of data scientists on data requirements, modeling approach, validation, statistical analyses, visualization and documentation.
  • Define best practices for modeling work including data integrity, data science best practice (e.g. version control and code-review), model quality and documentation of analytics development.

• Data Scientist, Bayer Crop Science (May 2016 - Nov 2019)

  • Delivered analytics solutions for the supply chain organization by developing an end-to-end pipeline from data ingestion, model selection and validation, to reporting for business partners.
  • Independently responsible for technical tasks including data wrangling, exploratory analyses, data querying (e.g. using different internal API’s and database query), model building and validation, code refactoring, building multiple visualization tools, and documentation.
  • Learned and assessed analytics platforms such as Domino data lab, AWS, Datarobot and Sagemaker.
  • Organized internal data science educational programs such as Python data wrangling workshops, participated in data science hackathon, and presented at internal symposiums and conferences.

• Analytics Co-Op, Monsanto Co. (Jan - July 2015)

  • Developed a change-point detection model for Monsanto’s first IoT platform to assess data quality for combine harvesters, and mitigate data loss of plot information due to device failure.
  • Supported the deployment of real-time anomaly detection algorithm in FieldDrive’s framework through collaboration with IT, engineering and analytics teams.
  • Supported the model development for numerous microbial field trials by analyzing the ranking consistency of microbial products, and geospatial properties of the fitted results across a set of different models.

• Research Intern, Medical College of Wisconsin (part-time Jan 2012 - Jan 2014)

  • Worked closely with researchers at the Max McGee Research Center for Juvenile Diabetes to develop quantitative algorithms to select genetic markers associated with early-onset type one diabetes based on data from human clinical trials.
  • Provided technical support for progress reports for grants, clinical programs, and academic journal articles.

• Research Assistant, University of Wisconsin- Milwaukee (2014)

  • Designed, implemented, and evaluated an Expectation Maximization (EM)-based parameter estimation algorithm for correlated random field with missing observations.
  • Presented at mathematical conferences and participated at several applied math workshops.

Education

• Master of Business Administration, Olin Business School, Washington University in St. Louis (Dec 2019)

• Consulting experience: Taylor community project partnered with UnitedWay to provide consulting services for local non-profit facing business issues and problems.

• Ph.D, Mathematics, University of Wisconsin - Milwaukee

• Dissertation: Parameter Estimation for Spatial Sampling Schemes with Missing Observations

• M.S., Mathematics, University of Wisconsin - Milwaukee

• Thesis: A Study of the Mathematical Modeling of Translation Initiation in Protein Synthesis.

Technical Skills

• Statistical modeling: Parameter estimation, ANOVA, hypothesis testing, multivariate statistics, parametric and non-parametric modeling, time-series analysis, survival analysis, functional data analysis, spatial statistics, anomaly detection methods, principal component analysis, multi-dimensional scaling

• Machine learning: Feature engineering, supervised and unsupervised learning, ensemble modeling, model selection and validation, natural language processing

• Tools/ Programming lanauges learned: Python, R, RShiny, Spark, Domino platform, Microsoft Azure, QGIS, MATLAB, SPSS, SQL, HTML/CSS, LaTeX, Markdown, Spotfire, Tableau, Excel, Sway, MS office suite

• Foreign spoken languages: Mandarin, Cantonese, Shanghainese

• Certificates: Passed actuarial exam P/1, 2009

Outreach, Leadership and Teaching Experience

• Adjunct Instructor, Washington University in St. Louis (Spring 2019 - Present)

• Currently teaching graduate-level statistic course (Linear Statistical Models) as part of the M.A. in Statistics program.

• Board member, Women in Data Science (WiDS) St. Louis (Fall 2019 - Present)

  • Responsible for organizing an annual WiDS St. Louis conference in collaboration with a small group of committee members that are enthusiastic about brining more visibility to women doing great work in the field of data science.

• LaunchCode Data Science Mentor (2016 - 2019)

  • Led weekly hands-on sessions on python machine learning for Launchcode’s CoderGirl program - a non-profit effort to make technical skills training more accessible for under-represented communities.

• Graduate Research Mentor, University of Wisconsin - Milwakee (Fall 2011 - Fall 2014)

  • Mentored six groups of undergraduate research fellows through an NSF-funded program in bio-mathematics.
  • Our research group focused on projects at the interface of mathematics applied to ranging from quantitative ecology to fresh water science.
  • Students also presented their work at national research conferences such as National Conference for Undergraduate Research (NCUR), Annual Undergraduate Research Conferences at the Interface of Biology and Mathematics, (NiMBiOS), Mathematical Association of America (MAA) and Joint Math Meetings (JMM). Many of students from our group went on to pursue graduate studies in highly quantitative fields.

Papers, Publications and Presentations

Talks and poster presentations:

• “Data Science for Sustainable Agriculture (talk)”, Women in Data Science Conference, Washington University in Saint Louis, St. Louis, MO. (2018)

• “How Leading Organizations are Solving the ModelOps Challenge (joint talk)”, Domino DataLab Webminar (2018)

• “Estimating parameters for the spatial Ornstein-Uhlenbeck process with missing observations (talk)”, Joint Mathematics Meetings, Seattle, WA. (2016)

• “Gene Selection from Microarray Data : An Exploratory Approach (poster presentation)”, Society of Industrial and Applied Mathematics (SIAM) Annual Meeting, Chicago,IL. (2014)

• “Serum Signature Analysis of Participants of the Anti-Interleukin-1 in Diabetes Action (AIDA) Trial (contributed abstract, talk given by Dr. Martin Hessner)”, American Diabetes Association 73rd scientific sessions, Chicago,IL. (2013)

• “Network Analytics and Visualization in Healthcare (joint talk)”, Mathematical and Statistical Modeling Workshop for Graduate Students, Statistical and Applied Mathematical Institute (SAMSI)/ N.C. State University.(2013)

• “Parameter Sensitivities and Markov Chain Models (joint talk)”, Joint MBI-NIMBioS-CAMBAM Summer Graduate Workshop on Stochastics Applied to Biological Systems, The Ohio State University. (2012)

• “Parameter Estimation: the Basics!”, MAA Mathfest, “Great Talks for a General Audience”, Madison,WI.(2012)

• “A Study of the Mathematical Model of Protein Synthesis Initiation”, MAA WI Chapter Meeting, Milwaukee School of Engineering. (2012)

• “A Study of the Mathematical Modeling of Protein Synthesis”, MAA WI Chapter Meeting, University of Wisconsin-Stout (2012)

• “Appearance of Surface Color during Simulated Twilight”, National Conference on Undergraduate Research, University of Wisconsin-La Crosse (2009)

Papers:

• Chen, Y. et. al, Molecular signatures differentiate immune states in Type 1 Diabetes families, Diabetes. 2014 Apr 23.

• Bradley, W.T., Chatterjee, S., Cheong, S., Huang, S., Lois, B., Poddar, A., Network Analytics and Visualization in Healthcare, CRSC-TR13-09 .