About Freshr
Based in Dartmouth, Nova Scotia, Freshr is an award-winning biomaterials and sustainable packaging company developing active packaging solutions that extend the shelf life of fresh proteins, starting with seafood. Freshr’s work sits at the intersection of food science, materials innovation, sustainability, helping reduce spoilage, protect product quality, and meaningfully reduce food waste.
As Freshr advances toward Series A readiness and commercial deployment, the company is strengthening the scientific, technical, and data foundation required to validate, optimize, and scale its technology. This is a pivotal stage of growth: the work is highly applied, deeply collaborative, and directly connected to solving one of the food industry’s most persistent challenges; keeping fresh food fresher, longer, with less waste.
About the Role
Freshr is seeking a Research Data Scientist to become its first dedicated data hire. Reporting to senior management, this role will help build the company's data strategy and analytical approach for biologic extraction work. The successful candidate will work closely with lab, engineering, and leadership teams to improve how experimental data is designed, captured, analyzed, validated, documented, secured, and used to guide technical and business decisions.
This is not a back-office analytics role. It is a practical, interdisciplinary role for someone who can bridge wet-lab science, process optimization, applied statistics, predictive modelling, and early-stage company execution. The work will help identify optimal extraction conditions, understand key process variables, and accelerate learning across Freshr's Design-Test-Learn cycle.
The Goal: Build the data discipline behind Freshr's next stage of R&D, experimental learning, and commercial readiness.
What You Will Do
Experimental Design & Optimization
· Collaborate with lab and engineering teams to apply Design of Experiments principles to R&D planning and execution.
· Design experimental runs that maximize statistical value while minimizing time, cost, and required wet-lab data.
· Apply statistical methods to identify optimal extraction conditions, improve data reliability, and recommend next experimental cycles.
Predictive Modelling & Data Analysis
· Develop and maintain predictive models that map relationships between process variables and outcomes such as capacity, yield, purity, quality, and cost.
· Apply appropriate modelling approaches for small, noisy, or limited datasets, reducing overfitting and strengthening confidence in results.
· Conduct sensitivity analyses to identify the variables with the greatest impact on process performance and business value.
· Communicate model outputs, assumptions, limitations, and recommendations clearly to technical and non-technical stakeholders.
Wet-Lab Integration, Data Governance & Documentation
· Develop standardized data collection templates, data dictionaries, workflows, and ingestion practices for R&D data.
· Maintain traceability of source data, transformations, assumptions, model outputs, and reproducibility steps.
· Prepare technical summaries, validation reports, data logs, and documentation to support funding, reporting, investor diligence, and IP-related needs.
· Act as a practical conduit between lab science, analytics, engineering, and business decision-making.
Data Tools & Scaling
· Establish practical data management and analysis tools suited to Freshr's current R&D stage.
· Recommend tools, platforms, and workflows that improve the speed and reliability of Design-Test-Learn cycles.
· Ensure early data structures can support future experimentation, pilot-scale production, reporting, and team growth.
· Bring hands-on experience with sensor hardware, IoT devices, or electrical prototyping as an asset, where applicable.
What You Bring
· Master’s degree or PhD in Data Science, Applied Statistics, Bioinformatics, Engineering, Computational Biology, Biochemistry, or a related field; equivalent applied experience may be considered.
· 2–5 years of experience applying data science, statistics, modelling, or machine learning to scientific, engineering, R&D, or experimental datasets.
· Strong applied statistics skills, including experimental design, model validation, interpretation, and responsible communication of uncertainty.
· Proficiency in Python and/or R, with experience using statistical modelling, visualization, and reproducible analysis tools.
· Ability to work with limited, noisy, or incomplete data and translate findings into practical recommendations.
· Clear communicator, strong documenter, collaborative problem-solver, and comfortable building structure in an early-stage technical environment.
Why Join Freshr?
At Freshr, your work will be close to the science, close to the decisions, and directly connected to the company's next stage of growth. This role offers the opportunity to build core data practices from the ground up, contribute to meaningful environmental innovation, and help shape how experimental learning supports commercial readiness. You will join a collaborative team focused on practical science, continuous learning, and creating real-world impact.
Pay: $75,000.00-$100,000.00 per year
Benefits:
- Company events
- Dental care
- Disability insurance
- Discounted or free food
- Employee assistance program
- Extended health care
- Life insurance
- Mileage reimbursement
- On-site parking
- Paid time off
- Relocation assistance
- Vision care
- Wellness program
Education:
- Master's Degree (required)
Work Location: In person
