Job Title: Field Statistician (Contractor)

Reporting to: Lead, Decision Science

Location: Durham, North Carolina or Remote


About Pairwise:

Pairwise is a mission-driven, food+tech company dedicated to building a healthier world through better fruits and vegetables. Pairwise was founded in 2017 by scientists at Harvard University, MIT, and Broad Institute who are eminent in the field of gene editing, as well as biotechnology industry pioneers. Our team is tuned in to consumer food trends, and we believe that consumers deserve more variety and innovation in their fresh food choices. We are primed to deliver that innovation through one of the best gene-editing platforms in food and agriculture. Pairwise has an exclusive 5-year research collaboration with Bayer to develop products in corn, soybean, wheat, canola, and cotton. Plus, Pairwise is developing new types of leafy greens, berries, and stone fruit, with the first product expected in 2023. Pairwise is based in the start-up friendly Research Triangle Park area of North Carolina.


About This Role:

We are looking for a Field Statistician to join our Decision Science Team who has an interest in performing experimental design, statistical analysis and predictive agronomic modeling to make data driven recommendations. This is a contract role that will work closely with interdisciplinary scientists, domain experts and stakeholders to define problems, and present analytic findings. We are looking for a collaborative, team-oriented scientist with a PhD, or equivalent level of training, that is motivated by a desire to integrate datasets to help understand and predict the complex interplay between genetics, environment and agronomic growing practices. This role’s contribution will be critical in helping Pairwise meet its goals and furthering the advancement of pipeline.


Essential Functions:

• Drive experimental design and statistical analysis to make data driven recommendations.

• Design and develop agronomic models to diagnose and predict patterns of crop performance using statistical modeling, process modeling, and other techniques such as machine learning.

• Strong communication skills to present work to diverse audiences.

• Assist with the design of field trial protocols.

• Analyze and judge the quality of data working closely with the field trials team.

• Create reports and dashboards in a timely and concise manner that will allow for rapid advancement decision making.

• Provide technical contributions in a fast-paced team environment to accelerate our efforts on building an analytics-driven product pipeline.

• Collaborate with universities and other scientific organizations to bring diverse thought into Pairwise.


Job Requirements:

• PhD, or equivalent experience in Statistics, Math or related quantitative fields.

• Experience using R, Python or other statistical and/or mathematical programming packages.

• Strong proficiency in data visualization and predictive modeling.

• Demonstrated ability to deliver scientific results in a cross functional environment.

• Experience with AWS computing/storage, snakemake, and Docker are a plus but not required.

• Ability to deliver scientific results in a collaborative, cross-functional environment.


Offerings:

• Casual work environment.

• Mission-driven organization focused on creating healthier fruits and veggies.

• A cutting-edge, driven community looking to lead the industry in innovation and nutrition.


EEO Statement:

We're an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.


Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At Pairwise we are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.