Apply for Job Job ID362111 LocationTwin Cities Job FamilyInformation Technology Full/Part TimeFull-Time Regular/TemporaryRegular Job Code9702DS Employee ClassAcad Prof and Admin Add to Favorite Jobs Email this Job About the Job Date: Application review will begin July8. This position is open for application until filled Classification & Title: 9702DS, IT Pro 2 - Data Science Working Title: GEMS Data Scientist Percent time: 100% Full-time Term: 12 month continuing appointment, annually renewable Department: GEMS Informatics Center Reports to: Kevin Silverstein Campus location: Cargill Building, St. Paul Campus PROGRAM / UNIT DESCRIPTION The GEMS Informatics Initiative, a joint CFANS and MSI (Minnesota Supercomputing Institute) agri-food informatics initiative of the University of Minnesota, is supported by a highly diverse international and interdisciplinary team of professionals. GEMS is re-imagining the relationships between data, institutions, and disciplines to inform and accelerate innovation within the food and agricultural sectors. GEMS makes genomics, environmental, management, and socioeconomic data inter-operable at varying spatial and temporal scales to generate actionable information and promote new innovation partnerships that accelerates and sustains growth in local and global food and agricultural systems. In CFANS, the initiative is directed by the GEMS Informatics Center. GEMS has five program areas: 1. GEMS Platform: Data sharing and analysis platform 2. GEMS Sensing: Field-based IoT (Internet of Things) sensors and data services 3. GEMS Exchange: Data streaming services via interoperable APIs 4. GEMS Learning: Digital and data science education 5. GEMS Solutions: Consulting services POSITION RESPONSIBILITIES We require a capable and creative data scientist with extensive experience in machine learning utilizing large-scale spatial data sets. Candidates should have dual facility with professional programming practices and also with data analysis that include the Genetics x Environment x Management x Socioeconomic domains that GEMS covers. In this role, he/she will spend most of the time translating conceptual predictive analytic tasks into practical machine learning solutions. Given the data-centric nature of this position, a strong facility with ML algorithms and computational methodology will be critical. * 80% Conducting data analysis to extract knowledge and insights from complex, high dimensional and/or high-volume data sets. Collaborating with stakeholders (primarily PepsiCo and Minnesota Department of Agriculture) to define and document business needs and requirements. Preparing data streams for use in predictive analytic applications. Identifying, examining, and analyzing the processes, procedures, and work practices of the problem at hand to efficiently meet project requirements. Utilizing project management techniques, principles, and methodologies to devise project plans, allocate resources, and oversee project execution. Applying cutting-edge machine learning algorithms toward applications in the agrifood sector using temporal and spatial data such as remote sensing, ground sensing, phenotypic and socio-economic data. Engaging in the process of writing code, utilizing Python language's versatile syntax to create efficient and functional programs. Additionally, tackling the crucial task of debugging and troubleshooting, skillfully identifying, and resolving errors and ensuring the smooth operation and optimal performance of the developed code using techniques like code review. At the end of the project, deploying the machine learning code through suitable approaches such as standalone application, web service/API, containerization, edge deployment, etc. while ensuring acceptable quality and integrity of the system. Identifying and assessing ineffective processes, suggesting alternative methods such as modifying or developing new procedures to aid and investigate complex computational problems in ag i-food research. * 20% Preparing reports based on analytic findings that propose changes in existing practices, highlighting the limitations of the analysis methods. Serving as a primary point of reference and information, offering guidance and support in the decision-making process of system projects. Composing technical documentation for purposes of reference and reporting. Qualifications REQUIRED QUALIFICATIONS * BA/BS plus at least two years of experience, or master's degree in Data Science, Computer Science, Statistics or related field * Experience working with structured/unstructured data/ time series data, applying statistical techniques and reporting results. * Advanced proficiency in Python and R * Experience with geospatial libraries such as geopandas and xarray, machine learning libraries such as Tensorflow, Keras, scikit-learn and visualization libraries such as seaborne * High degree of comfort working within the UNIX/LINUX shell environment. * Excellent oral and written communication skills * Able to work independently with periodic guidance PREFERRED QUALIFICATIONS * Masters degree in related field and 2+ years of data science experience such as working with structured/unstructured data/ time series data, applying statistical techniques and reporting results * Experience working on projects involving the agricultural, biological or environmental sciences * Experience in batch scheduled environments (slurm, torque, SGE, etc.) * Proficiency in SQL * Experience with git or similar source control management system. * Experience developing end to end machine learning systems * Demonstrated attention to detail and proactivity * Strong inclination to collaborate in a team environment Benefits Working at the University At the University of Minnesota, you'll find a flexible work environment and supportive colleagues who are interested in lifelong learning. We prioritize work-life balance, allowing you to invest in the future of your career and in your life outside of work. The University also offers a comprehensive benefits package that includes: Competitive wages, paid holidays, and generous time off Continuous learning opportunities through professional training and degree-seeking programs supported by the Regents Tuition Benefit Program Low-cost medical, dental, and pharmacy plans Healthcare and dependent care flexible spending accounts University HSA contributions Disability and employer-paid life insurance Employee wellbeing program Excellent retirement plans with employer contribution Public Service Loan Forgiveness (PSLF) opportunity Financial counseling services Employee Assistance Program with eight sessions of counseling at no cost Employee Transit Pass with free or reduced rates in the Twin Cities metro area Please visit the Office of Human Resources website for more information regarding benefits. How To Apply Applications must be submitted online, and include a cover letter and resume or CV. To be considered for this position, please click the Apply button and follow the instructions. You will be given the opportunity to complete an online... For full info follow application link. The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission. The University is committed to attracting and retaining employees with varying identities and backgrounds. The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu.