The Department of Biological Systems Engineering at the University of Nebraska-Lincoln (UNL) Institute of Agriculture and Natural Resources (IANR) is seeking an Agricultural Data Scientist at the rank of Research Assistant Professor. This 12-month non-tenure track position involves 100% research apportionment, collaborating with an interdisciplinary team to develop data collection and analytical tools aimed at advancing agricultural production systems. Key responsibilities include developing hardware and software platforms for data collection and analysis, securing extramural funding, and publishing research findings. Required qualifications include a Ph.D. in a relevant field and demonstrated research experience. This position, located in Lincoln, Nebraska, offers an opportunity to contribute to cutting-edge agricultural research and support the land-grant mission of IANR. For comprehensive interview preparation, explore Interview Query for valuable insights and tips.

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining the University of Nebraska-Lincoln (UNL) as an Agricultural Data Scientist. Whether you were contacted by a UNL recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the University of Nebraska-Lincoln's Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the UNL data scientist hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for the UNL Agricultural Data Scientist role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around UNL’s data systems, ETL pipelines, and SQL queries.

In the case of data scientist roles, take-home assignments regarding product metrics, analytics, and data visualization are incorporated. Apart from these, your proficiency against hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed during the round.

Depending on the seniority of the position, case studies and similar real-scenario problems may also be assigned.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at UNL's office. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the Agricultural Data Scientist role at UNL.

Quick Tips For University Of Nebraska-Lincoln Agricultural Data Scientist Interviews

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your UNL interview include:

• Know Your Agricultural Data: Given the specialized nature of the role, understanding agricultural crop production systems and data sets related to precision agriculture is crucial.
• Be Data-Driven: UNL’s data science interviews assess how well you can provide insights with various datasets. Brush up on your knowledge of data statistics, programming languages, and analytical software.
• Embody the Mission: UNL values creativity, inclusivity, and innovation. Practice responding to behavioral questions with answers that reflect those values and highlight your ability to work within diverse, interdisciplinary teams.

Typically, interviews at University Of Nebraska-Lincoln vary by role and team, but commonly Data Scientist interviews follow a fairly standardized process across these question topics.

• Write a function to find and return the last node of a singly linked list. You are given a singly linked list. Write a function to find and return the last node of the list. If the list is empty, return null.

• What metrics would you use to determine the value of each marketing channel for Mode? Mode sells B2B analytics dashboards and has various marketing channels with respective costs. Identify the key metrics to evaluate the value of each marketing channel.

• How would you measure the success of Facebook Groups? Determine the key metrics and methods to evaluate the success and effectiveness of Facebook Groups.

• What key parameters would you focus on to improve customer experience on Uber Eats? Identify the main parameters that should be improved to enhance the customer experience on Uber Eats.

• How would you measure success for Facebook Stories? Specify the metrics and criteria you would use to measure the success of Facebook Stories.

• What do you think are the most important metrics for WhatsApp? Identify the most critical metrics to evaluate the performance and success of WhatsApp.

• How would you interpret coefficients of logistic regression for categorical and boolean variables? Explain how to interpret the coefficients of a logistic regression model when dealing with categorical and boolean variables.

• How would you interpret coefficients of logistic regression for categorical and boolean variables? Explain how to interpret the coefficients of logistic regression when dealing with categorical and boolean variables.

• What are the assumptions of linear regression? List and describe the key assumptions that must be met for linear regression to be valid.

• How would you tackle multicollinearity in multiple linear regression? Describe the methods you would use to identify and address multicollinearity in a multiple linear regression model.

• How would you encode a categorical variable with thousands of distinct values? Explain the techniques you would use to encode a categorical variable that has thousands of distinct values.

• How would you handle data preparation for building a machine learning model using imbalanced data? Describe the steps you would take to prepare data for a machine learning model when dealing with imbalanced classes.

What is the average salary for a Data Scientist at University Of Nebraska-Lincoln?

Q: What are the main responsibilities of the Research Assistant Professor - Agricultural Data Scientist position? The key responsibilities include collaborating with an interdisciplinary team to develop data collection and analytical tools, creating IoT and embedded systems, analyzing data from agricultural field equipment and research systems, and developing software tools for generating actionable reports. Securing extramural funding and publishing research findings are also essential duties.

Q: What qualifications are required for the Agricultural Data Scientist position at the University of Nebraska-Lincoln? Candidates must have a Ph.D. in Biological Systems Engineering, Agricultural Engineering, Food Engineering, Computational Sciences, or a closely related field. They should also have demonstrated research experience in experimental data collection, post-processing, and statistical analysis with a track record of peer-reviewed publications.

Q: What makes this position unique in terms of research and collaboration? This role is unique due to its interdisciplinary nature, involving collaboration with agricultural engineers, agronomists, economists, statisticians, and computer scientists. The position also emphasizes the development of advanced research tools and data systems for precision agriculture, offering ample opportunities for innovation and impact in the field.

Q: How do diversity and inclusivity play a role in this position? The Institute of Agriculture and Natural Resources (IANR) and the Department of Biological Systems Engineering are committed to creating inclusive learning, research, and working environments. This aligns with the University’s N2025 Strategic Plan, which treats every interaction as essential to collective well-being and mission delivery. Candidates are expected to support these diversity and inclusivity initiatives.

Q: How can I prepare for an interview for this position? To prepare, research the University of Nebraska-Lincoln and the Department of Biological Systems Engineering. Practice common interview questions relevant to data science and agricultural systems. Review your technical skills and consider how your past experiences align with the job duties. Utilizing Interview Query can significantly help in fine-tuning your preparation and boosting your confidence.

If you're aspiring to join the University of Nebraska-Lincoln as an Agricultural Data Scientist, our University Of Nebraska-Lincoln Interview Guide is your go-to resource. Dive deep into the specific questions and scenarios that could be presented. You can also explore interview guides for roles like software engineer and data analyst, covering UNL’s unique interview process.

At Interview Query, we empower you with the insights, strategies, and confidence necessary to excel in your interview. Access our extensive collection of company interview guides and connect with us for any additional support you need.

Best of luck with your interview at University of Nebraska-Lincoln!