Data Scientist Intern

Erlanger, KY

We are looking for a Data Scientist Intern to join our Artificial Intelligence Team and work with our team of data scientists in developing models within an Azure ecosystem. They must have strong experience using various data mining and analysis methods, using multiple data tools, building and implementing models, using/creating algorithms, and creating/running simulations. This position may partner with many businesses and product and science teams, so written and in-person communication skills are critical. They must be comfortable working with various stakeholders and functional groups. The right candidate will be passionate about building engineering solutions supporting the latest advances in artificial technology. We have many different functions in the team, and this role requires a broad range of skills, such as machine learning, data, optimization, and platform/infrastructure engineering.

At ADM, we unlock the power of nature to provide access to nutrition worldwide. With industry-advancing innovations, a complete portfolio of ingredients and solutions to meet any taste, and a commitment to sustainability, we give customers an edge in solving the nutritional challenges of today and tomorrow. We are a global leader in human and animal nutrition and the world’s premier agricultural origination and processing company. Our breadth, depth, insights, facilities, and logistical expertise give us unparalleled capabilities to meet food, beverages, health, and wellness needs. From the seed of the idea to the outcome of the solution, we enrich the quality of life the world over.

Key Responsibilities:

  • In this role, you are required to use advanced modeling techniques and have the strong business acumen to deliver data-driven, actionable insights and recommendations to address our global business challenges
  • Present compelling, validated stories to peers, management, and internal customers to drive both strategic and operational changes in business
  • Work independently to structure analyses and develop insights. Organize material to facilitate reviews, quality checks, and presentation of findings
  • Manage modeling processes from end to end, including data gathering, validation, model building, calibration, cross-validation, and maximizing model accuracy. Interpret and validate model results with statistical checks. Design reports, data visualizations, and presentations to track model performance and communicate business impact to leadership teams
  • Explain complex modeling approaches in simple terms; Develop compelling narratives that connect modeling results with business challenges
  • Build and maintain strong working relationships based on trust and mutual respect. Communicate with managers to balance stakeholder and analytics perspectives
  • Adept at quickly acquiring software skills

Standard Job Requirements:

  • Working knowledge of supervised (GLM, Classification models, Ensemble techniques, Regularization techniques, Bayesian Models, Hierarchical models, etc.) and unsupervised models (Clustering, Principal Component Analysis, etc.)
  • Solid programming skills in Python, and R, with solid SQL skills
  • Model development experience in an Azure environment is highly preferred
  • Experience working with enterprise-scale databases, with demonstrated ability to independently query and prepare data for analysis
  • Self-directed, innovative thinker. In addition to strong attention to detail, strong candidates will also be able to see the strategic implications for the business in the big picture. You are fluent in telling the story to both technical and non-technical audiences
  • Strong candidates will have a curious mind, a passion for synthesizing information from multiple sources, the ability to interpret data through the lens of customer behavior, and a habit of translating data into insights that drive action
  • Demonstratable knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
  • Demonstratable knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, proper usage, etc.) and experience with applications
  • Strong business aptitude, the ability to rapidly learn new problem domains, and become conversant in the field with subject matter experts 
  • Creative, proactive, bold, and out-of-box thinking
  • Great curiosity, high enthusiasm, integrity, ingenuity, results-orientation, self-motivation, and resourcefulness in a fast-paced competitive environment

Educational Requirements:

  • Pursuing a degree in a quantitative discipline (e.g., data science, statistics, applied mathematics, or economics).

ADM is an EOE for minorities, females, protected veterans, and individuals with a disability.

Subscribe to Job Alerts