About Matthew Martz¶
My expertise is in building and leading teams of Data Scientists, Machine Learning Engineers, Data Engineers, and Data Product experts of diverse experience levels, distributed across cultural and knowledge bases, to drive innovation, product development, and cutting edge, actionable research. I have a proven track record of mentoring, growing, executing, and building strategy around ambitious goals across the Data Science technical platform to provide business value.
My background is in Quantitative Cell Biology and I have a PhD in Biochemistry and Molecular Biology. I spent much of my career researching novel cancer therapeutics through live cell imaging and machine learning. You can now find me developing and implementing machine learning platforms and algorithms for everything from optimization problems to precision medicine and medicinal AI. In recent years I have researched and built novel recommenders, 24/7 production machine learning solutions, and received patents for personalization solutions in the consumer sales space and chemical profile recommenders.
Most recently, I have been working in the Biotechnology space where I have developed the long-term strategy and vision for Data Science, led a growing team of Data Scientists to develop novel algorithms in the predictive modeling and Bioinformatics spaces, and accelerated biological discovery. Moreover, I designed and implemented novel algorithms to detect differential modes of action in both natural products and whole microbe systems, and engineered a proprietary online learning platform to serve as an artificial intelligence decision guidance system for our extensive microbial collection and proprietary product discovery platform (Genesis), a digital twin.
Find more about me here: About Matthew Martz
Currently
TRAIT DISCOVERY AND DELIVERY PROGRAM LEAD
DIGITAL BIOLOGY LEAD (traits)
BENCHLING RESEARCH PIPELINE TECHNICAL LEAD
[Details to come]
Previously
DIRECTOR OF DATA SCIENCE/ML/AI AND TECHNICAL LEAD/STRATEGIC VISION
Served as Director of Data Science/Machine Learning/Artificial Intelligence strategy and innovation initiatives.
Led a growing team of Data Scientists working to drive biological research and accelerate product development.
Team size ranged from 7 to over 20, across disciplines of Data and Product.
Developed and drove 4 year strategy and vision for Data Science, Data Engineering, Bioinformatics, and Data Product for entire organization.
Advocate and conduct learning around Data Science/ML/AI products and platforms both to internal teams, executive team and board members, and external partners and collaborators (customers).
Directly contributed to high impact publications and invited for speaking engagements.
Served as Data Science liaison across the company, communicating strategy, accomplishments, initiatives, and best practices. Developed the long-term Data Science strategy and vision, hiring plan, technological innovation pipeline, and overall project management for the department.
Developed a proprietary predictive artificial intelligence decision guidance system to serve as a core to our proprietary natural and whole microbe product discovery platform - GENESIS, a digital twin technology. This digital twin technology has already generated a large corpus of actionable research, product leads, and accelerated screening paradigms to put the best leads in the field. Excitingly, my team was able to harness GENESIS to generate cross-indication predictive models to drive and accelerate lead identification across the research platform.
Led Data Science contribution to external manuscripts and internal white papers for both research, Data Science, and SOPs.
Sat on a team of technical leaders that drove research initiatives across the company and served as a hive mind to solve challenges across domains. Identified and addressed gaps in research and Data Science.
Developed a novel algorithm to use interpretable machine learning model ensembles to traverse genomic annotations and drive mode of action discovery from small datasets. Designed and developed a predictive modeling platform to accelerate product discovery in indication screening. Designed and developed a cross-indication prediction platform to enable multi-target identification.
Previously
HEAD OF DATA SCIENCE/ML/AI AND PRINCIPAL, RESEARCH AND MACHINE LEARNING
Created and maintained the core, patented algorithms behind the Firstleaf wine club.
I built and led a local and distributed team of Data Scientists and Machine Learning engineers (The Research and Machine Learning Team) developing machine learning and AI platforms to drive real time recommendations, inform business strategy, and create/integrate with product design life cycle. This included the end-to-end development of the ML stack using both traditional ML and cutting edge deep learning techniques including computer vision, generative AI, and NLP, along with novel algorithm development.
Team size ranged from 5 to 10, across disciplines of Data and Product.
I was further responsible for the continual growth of the team, maintaining stakeholder communication, driving Data Science strategy across the organization, and directly working with C-level executives to maintain a vision and communicate strategy and execution plans aligned with business executives.
The Research and Machine Learning team was responsible for identifying and developing key Data Science and Machine Learning technologies for Firstleaf. We utilized cutting edge approaches to both empower internal company function as well as customer facing products. The team was also responsible for design and implementation of the patented (developed technologies, co-write and secured patents) algorithms that drove the Firstleaf experience. The team was responsible for initiating, driving, and executing on data science strategies across Marketing, Finance, Business Intelligence, and Wine Making functions – the Research and Machine Learning team was a full spectrum B2B and B2C solution within Firstleaf.
Expertise
Predictive Modeling | Medicinal AI | Machine Learning | Algorithm Development | Technical Writing | Leadership | Mentorship | Team Building | Cross-departmental Collaboration | Data Science | Artificial Intelligence | Python/Software Engineering | Cell Biology | Biophysics | Microscopy | Cancer Therapeutics | E-commerce | Manuscript and Grant Preparation | Patent Development | Bioinformatics | Microbiology | Crop Protection | AgTech | Biotechnology | Strategy and Vision Building | Resource Allocation | Multimodal Modeling
Experience
Digital Biology Lead at Syngenta
Head of Data Science/ML/AI and Technical Lead / Strategic Vision at AgBiome
Head of Data Science and Principal, Research and Machine Learning at Penrose Hill/Firstleaf
BS in Biochemistry and Molecular Biology, The Pennsylvania State University
PhD in Biochemistry and Molecular Biology, Thomas Jefferson University
Research Postdoctoral Fellow, Lineberger Cancer Center, University of North Carolina at Chapel Hill
21 years of Software Engineering and Data Science experience
17 years of rigorous scientific training in academic programs
8+ years of Data Science and Machine Learning leadership
Industry proven leader in Data Science and Machine Learning
Mutaku is a collection of writings across the spectrum of biomedical research, software engineering (Python), Machine Learning, and Data Science.