JOB TITLE: Data Analyst -Tidal Grow AgriScience
REPORTS TO: Tidal Grow AgriScience Chief Product Officer
LOCATION: Argentina, Brazil, Puerto Rico, or India
SALARY RANGE: based on location & overall experience
About Tidal Vision:
We believe that sustainability should not require customers to compromise on price, convenience, or performance. Our mission is to create positive and systemic environmental impact by making our biopolymer solutions cost competitive, more convenient, and better performing than the synthetic chemicals we displace. We value innovation and take pride in challenging the status-quo; we choose to view obstacles as opportunities. We value new ideas and encourage the team to apply creativity and invent new solutions to meet challenging demands. We foster open, direct communication, and a collaborative working environment through our unique approach to work culture. We value our employees and demonstrate that through our compensation and benefits programs and opportunities for growth and development.
About Tidal Vision’s Unique Work Culture:
Tidal Vision strives to build and invest in the highest performing and most innovative team. We put our people and customers above process, avoid company-wide rules as much as possible, and have the courage to take unusual approaches to advance our mission. With this approach, we believe we can create a more flexible, fun, stimulating, creative, collaborative, and innovative organization.
Our commitment to developing, practicing and promoting direct and open communication, responsibility and freedom, and leading with and seeking context is a responsibility for every role at Tidal Vision.
JOB SUMMARY:
This position supports the Tidal Grow AgriScience division of Tidal Vision Products. Partnerships between the R&D and the Ag Commercial teams is critical to this role’s success. The ideal candidate will have experience working with Randomized Complete Block Design (RCBD) trials, grower trials, and spatial analytics, combined with proficiency in data cleaning, modeling, and the use of advanced analytical tools like PowerBI and SQL. This role offers an opportunity to work in a dynamic, data-driven environment, where you will contribute to the optimization of
agricultural processes to bring novel, environmentally friendly solutions to help solve agriculture’s greatest challenges.
ESSENTIAL JOB FUNCTIONS:
- Data collection and management
- Collect, clean and preprocess complex agronomic data from small plot trials, grower trails, and other field experiments.
- Ensure data integrity and consistency across different databases.
- Trail Design & Analysis:
- Analyze RCBD small plot trails and grower trails to evaluate various agronomic factors and crop performance.
- Provide insight on trial design and optimize efficiency and accuracy of experiments.
- Spatial Analytics:
- Conduct spatial analysis to assess field variability and identify patterns that affect crop performance, yield predictions, and resource management.
- Data Modeling and Statistical Analysis:
- Utilize statistical models, including Principal Component Analysis (PCA), regression models, and other advanced techniques to interpret trial data and generate actionable insights. Build predictive models to forecast outcomes and identify key variables impacting trial results.
- Data Visualization and Reporting:
- Develop interactive dashboards and visualizations using PowerBI to communicate complex agronomic findings to stakeholders. Prepare detailed reports summarizing statistical analysis, trends, and recommendations.
- Collaboration and Support:
- Work closely with Product, R&D, and Agronomy teams to ensure accurate data collection and interpretation. Support cross-functional teams with data-driven insights to inform decision-making processes. Operationalize best practices to support scalability across the organization.
- Database Management:
- Develop and maintain SQL-based databases to store, query, and manage large agronomic datasets. Ensure efficient data storage and retrieval methods for scalability.
BASIC QUALIFICATIONS:
- Bachelors or Masters degree in Agronomy, Agricultural Science, Data Science, Statistics, or related field.
- 3+ years experience with RCBD trial designs and analysis, specifically in the context of agricultural research or grower trials.
- 3+ years xperience with spatial analytics and mapping tools for field data interpretation.
- Proficiency in Principal Component Analysis (PCA) and other statistical modeling techniques for multivariate data analysis.
- Hands-on experience cleaning and structuring large datasets, building data models, and generating insights from raw data.
- Strong background in PowerBI for creating dashboards and visualizing data trends.
- Proficiency in SQL for data querying, manipulation, and database management.
- Knowledge of agronomy practices, crop production, and grower trial methodologies.
- Must speak fluent English.
- Must be willing to travel 15%.
PREFERRED QUALIFICATIONS:
- Experience with statistical software such as R, Python, or SAS.
Licensing & Special Requirements
- Incumbent is subject to a criminal background check
WORKING CONDITIONS & PHYSICAL REQUIREMENTS
Most of the work is performed in an office environment and outdoors in inclement weather. Candidates must be able to stand and/or walk for long periods of time.
Tidal Vision provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
The statements contained herein reflect general details as necessary to describe the principal functions of this job, the level of knowledge and skill typically required, and the scope of responsibility, but should not be considered an all-inclusive listing of work requirements. Individuals may perform other duties as assigned including work in other functional areas to cover absences or relief, to equalize peak work periods, or otherwise to balance the workload. Furthermore, they do not establish a contract for employment and are subject to change at the discretion of the employer.
Key Responsibilities:
Data Collection and Management:
Collect, clean, and preprocess complex agronomic data from small plot trials,
grower trials, and other field experiments. Ensure data integrity and consistency
across different datasets.
Trial Design and Analysis:
Analyze RCBD small plot trials and grower trials to evaluate various agronomic
factors and crop performance. Provide insights on trial design to optimize the
efficiency and accuracy of experiments.
Spatial Analytics:
Conduct spatial analysis to assess field variability and identify patterns that affect
crop performance, yield predictions, and resource management.
Data Modeling and Statistical Analysis:
Utilize statistical models, including Principal Component Analysis (PCA),
regression models, and other advanced techniques to interpret trial data and
generate actionable insights. Build predictive models to forecast outcomes and
identify key variables impacting trial results.
Data Visualization and Reporting:
Develop interactive dashboards and visualizations using PowerBI to
communicate complex agronomic findings to stakeholders. Prepare detailed
reports summarizing statistical analysis, trends, and recommendations.
Collaboration and Support:
Work closely with Product, R&D, and Agronomy teams to ensure accurate data
collection and interpretation. Support cross-functional teams with data-driven
insights to inform decision-making processes. Operationalize best practices to
support scalability across the organization.
Database Management:
Develop and maintain SQL-based databases to store, query, and manage large
agronomic datasets. Ensure efficient data storage and retrieval methods for
scalability.
Qualifications:
Education:
Bachelor's or Master's degree in Agronomy, Agricultural Science, Data Science,
Statistics, or a related field.
Experience:
Proven experience with RCBD trial designs and analysis, specifically in the
context of agricultural research or grower trials.
Experience with spatial analytics and mapping tools for field data interpretation.
Proficiency in Principal Component Analysis (PCA) and other statistical modeling
techniques for multivariate data analysis.
Hands-on experience cleaning and structuring large datasets, building data
models, and generating insights from raw data.
Strong background in PowerBI for creating dashboards and visualizing data
trends.
Proficiency in SQL for data querying, manipulation, and database management.
Skills & Abilities:
Strong analytical skills with the ability to interpret complex datasets and translate
findings into actionable recommendations.
Knowledge of agronomy practices, crop production, and grower trial
methodologies.
Experience with statistical software such as R, Python, or SAS is a plus.
Strong communication skills, with the ability to present technical findings to non-
technical stakeholders.
Self-motivated, proactive, and able to work independently as well as part of a
team.