Esther Meenken
Christchurch
Summary
With two decades of expertise in data science and statistics, I excel in transforming data into impactful narratives. My career has been marked by a profound commitment to transdisciplinary and ethical practices, particularly in collaboration with biological, social science and Mātauranga Māori researchers. I actively engage with research bodies, governmental policy makers, agri-tech industry leaders, and international digital innovation experts to drive positive outcomes from the worldwide digital revolution. My proficiency extends across the entire data lifecycle, from meticulous collection and governance to knowledge exchange and end-of-life strategies. I am dedicated to enhancing value and insights for New Zealanders.
Overview
20
20
years of professional experience
Work History
Senior Data Scientist
AgResearch
03.2017 - Current
- Worked with stakeholders to develop quarterly roadmaps based on impact, effort and test coordinations.
- Assessed accuracy and effectiveness of new and existing data sources and data analysis techniques.
- Discovered stories told by data to present information to scientists and business managers.
- Utilized advanced querying, visualization and analytics tools to analyze and process complex data sets.
- Coached and mentored data scientists, scientists, interns and phd students on SAS and data mining techniques.
- Devised and deployed predictive models using machine learning algorithms.
- Ran statistical analyses within software to process large datasets.
- Analyzed large datasets to identify trends and patterns.
- Developed polished visualizations to share results of data analyses.
- Applied loss functions and variance explanation techniques.
Statistician
Plant And Food Research
05.2005 - 03.2017
- Conducted quality checks on data sources to check for inconsistencies and perform data cleaning activities.
- Performed data cleaning and data preparation to support high-quality data and catch errors before processing.
- Developed statistical models for [Type] projects to analyze and represent tasks required to complete project.
- Prepared statistical analysis plans and provided statistical interpretation for graphs, tables and charts.
- Applied statistical methods to solve specific problems and managed assigned deliverables related to study.
- Evaluated statistical techniques and extracted [Type] information from research data to provide different ways to assess robustness of research outputs.
- Developed integrated spreadsheet and database templates for accumulating, formatting and organizing program data and presented findings to management.
- Skilled at working independently and collaboratively in a team environment.
- Self-motivated, with a strong sense of personal responsibility.
- Proven ability to learn quickly and adapt to new situations.
- Worked well in a team setting, providing support and guidance.
- Managed time efficiently in order to complete all tasks within deadlines.
- Demonstrated respect, friendliness and willingness to help wherever needed.
- Excellent communication skills, both verbal and written.
- Passionate about learning and committed to continual improvement.
- Proved successful working within tight deadlines and a fast-paced environment.
- Strengthened communication skills through regular interactions with others.
- Organized and detail-oriented with a strong work ethic.
- Used critical thinking to break down problems, evaluate solutions and make decisions.
- Adaptable and proficient in learning new concepts quickly and efficiently.
- Cultivated interpersonal skills by building positive relationships with others.
- Participated in team projects, demonstrating an ability to work collaboratively and effectively.
- Identified issues, analyzed information and provided solutions to problems.
- Developed and maintained courteous and effective working relationships.
- Worked with stakeholders to develop quarterly roadmaps based on impact, effort and test coordinations.
- Assessed accuracy and effectiveness of new and existing data sources and data analysis techniques.
- Discovered stories told by data to present information to scientists and business managers.
- Utilized advanced querying, visualization and analytics tools to analyze and process complex data sets.
- Coached and mentored data scientists, scientists, interns and phd students on SAS and data mining techniques.
- Devised and deployed predictive models using machine learning algorithms.
- Ran statistical analyses within software to process large datasets.
- Analyzed large datasets to identify trends and patterns.
- Developed polished visualizations to share results of data analyses.
- Applied loss functions and variance explanation techniques.
Guest Lecturer
University Of Canterbury
01.2010 - 12.2011
- Prepared and delivered lectures to [Type] students on [Type] and [Type] topics.
- Sharpened students' learning by focusing on selected core concepts and skills.
- Mentored and advised students to explore career pathways based and amplify knowledge, skills and strengths.
Statistician
Primary Industries Research Victoria
03.2004 - 03.2005
- Developed statistical models for animal capture-recatpure projects to analyze and represent tasks required to complete project.
- Assisted in field sampling
Education
Ph.D. - Statistics
University of Auckland
Auckland2016
Master of Science - Biometrics
Reading University
Reading, Berkshire, UK2007
Bachelor of Arts - Statistics
University of Otago
Dunedin2002
Bachelor of Science - Zoology
University of Otago
Dunedin2001
Skills
Transdisciplinary ways of working and: Integrating knowledge, methods and perspectives to address complex or wicked problems Fostering deeper, more unified connections across multiple disciplines, fields of expertise and non-academic stakeholders including communities, industry professionals and policy-makers to obtain a more comprehensive understanding of complex issues, ultimately leading to innovative and impactful solutions
Uncertainty: Bias and Precision, Epistemology, aleotory vs epistemic, interface between data and social disciplines in how data is used to make decisions, particularly but not only in the use of bio-physical process models
Statistical & Data science methods & algorithms: Bayesian statistics, Visualisation, Design of Experiments, Linear & Linear Mixed Models (LM, LMM), Generalised Linear, Mixed and Hierarchical Models (GLM, GLMM, HGLM (this includes logistic regression)), Nonlinear models, Generalised Additive Models, ARIMA (timeseries models), Multivariate statistics, XGBOOST and other decision tree methods, Technical and Operational: Programming/Software (R, GenStat, MatLab, PowerBI, Excel, SigmaPlot
FAIR CARE data principles: Data Governance Ethics, AI Ethics, Matauranga Maori Knowledge systems, Maori Sovereignty principles, Product owner/research lead for software development and data architecture including pipelines and instream analytics in research applications, on eR platform during development phases for open science software infrastructure
Digital Innovation and Integration of data and technologies
Timeline
Senior Data Scientist
AgResearch
03.2017 - Current
Guest Lecturer
University Of Canterbury
01.2010 - 12.2011
Statistician
Plant And Food Research
05.2005 - 03.2017
Statistician
Primary Industries Research Victoria
03.2004 - 03.2005
Ph.D. - Statistics
University of Auckland
Master of Science - Biometrics
Reading University
Bachelor of Arts - Statistics
University of Otago
Bachelor of Science - Zoology
University of Otago
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