Biostatistician

Objective

• Implement data analysis of experimental data through assay development and screening, present findings to internal stakeholders, scale ad-hoc analyses into prototype level analytics pipelines. Collaborate closely with statistical and data scientists, and with technical functions, CROs, and program teams to help build engineered microbial products for agriculture.

Responsibilities

• Experimental Design, Assay Development, and Assay Quality Analytics:  Create novel scientific insights and starting points by analyzing plant and lab data from multiple in vitro experiments and instruments, including but not limited to high throughput formats, colorimetric spectroscopy, protein quantification assays, growth curves, microscopy, dose responses, plant-microbe interaction, seed germination, leaf damage, etc.  Create standard analysis templates that enable programmatic and analytic best practice adoption.  Seek opportunities to improve methods, operations, and analyses by application of statistical or quantitative tools. Work with Data Science team to leverage statistical and modeling expertise.
• Data Analysis and Storytelling Across Pipeline Screening:  Apply modern data science and biostatistics tools for design and analysis of screening experiments to evaluate and rank biological performance of engineered microbes.  Structure and simplify complex scientific questions and approaches to link analytics strategy and outcomes datasets.  Communicate effectively through listening, documentation and presentations, especially using compelling visualizations to share analysis and interpretation of data.  Work with Data Science team to develop ad-hoc analyses into standardized and automated analysis pipelines. 
• Foster a culture of data-driven insights: Build relationships across the R&D departments and CROs including Ginkgo Bioworks, and build consensus based on data-driven insights.  Maintain a credible record of unbiased truth. Lead cross-functional data science teams to meet program timelines. Contribute to increasing the data fluency in Joyn Bio by mentoring others in data analysis concepts.  Inspire others with new approaches, your way of thinking, and the potential for data science to accelerate their work. 

Training/Experience

• M.S. or Ph.D. or equivalent with a scientific and quantitative focus – some examples include but are not limited to Biostatistics, Biology, Microbiology, Plant Biology (e.g. plant physiology, plant pathology, crop protection), etc with interest in data analysis and biostatistics. 
• Multiple years of industry experience (5+ years preferred) with strengths in several of the following: experimental design, assay development, statistical modeling.
• Experience with high throughput bioassays development and screening experiment design and analysis.
• Expertise in data visualization and data storytelling, presentation skills
• Strong communication skills, collaborative mindset and track record with cross-disciplinary functional teams.
• Build relationships across the R&D departments and CROs, and build consensus based on data-driven insights.
• Analytical skills and mindset to solve real-world problems with applied data science; enjoys structuring and simplifying complex problems.
• Experience with JMP, Tableau, R Shiny/Dash/Plotly/Kibana or other web-based interfaces to create graphic-rich data explorations, charts, data maps, etc.
• Exposure to R and python, command line usage
• Familiarity with modern data science tech stack and concepts (e.g. AWS, Git, Agile, APIs, SQL, etc).
• A passion for creating transformative agricultural products, discovering new ways to add value to farmers.

Organizational

• This position reports to the Data Science Lead.
• Joyn Bio welcomes applications from all individuals, regardless of race, national origin, gender, age, physical characteristics, social origin, disability, union membership, religion, family status, pregnancy, sexual orientation, gender identity, gender expression or any unlawful criterion under applicable law. We are committed to treating all applicants fairly and avoiding discrimination.

Location

• This position is based in Boston, Massachusetts and may accommodate flexible working arrangement.