Applied Data Scientist

Summary

Join Milk Moovement as an Applied Data Scientist to optimize agricultural supply chains using machine learning, statistical modeling, and mathematical optimization. You will design and implement data-driven systems, build predictive models, and collaborate with product and design teams. The ideal candidate has 5+ years of experience in similar roles, proficiency in Python and various data science frameworks, and experience solving real-world problems with data science. The role is fully remote but currently only accepting candidates from Newfoundland & Labrador, Canada. Milk Moovement offers competitive salaries, equity, unlimited paid vacation, health benefits, and a remote work environment with flexible hours.

Requirements

• Have built predictive models, performed regression analysis, and/or applied optimization techniques to drive business outcomes
• Be fluent in Python and common statistical and data science frameworks
• Have 5+ years of experience in similar roles
• Enjoy creating models and systems that deliver measurable impact for the business

Responsibilities

• Design and implement scalable data-driven systems to solve real-world operation challenges (e.g., scheduling, plant operations, financial forecasting), including pipelines for data ingestion, modeling (e.g., ML, optimization, statistical), deployment, and monitoring
• Use regression and classification models to uncover supply chain anomalies and inefficiencies
• Collaborate with product and design to ensure new intelligent, data-optimized features are embedded within the platform
• Stay current with advancements in data science and integrate new techniques as appropriate

Preferred Qualifications

• Experience designing and supporting end-to-end data science workflows—including model training, deployment, monitoring, and MLOps practices (e.g., CI/CD, Docker, model versioning)
• Proficiency in building and deploying models using frameworks such as Pandas, NumPy, TensorFlow, PyTorch, and Scikit-learn
• Demonstrated expertise in writing clean, modular, and efficient Python code, with a deep understanding of software engineering best practices including unit testing, packaging, performance profiling, and scalable architecture design
• Experience developing and applying models—including optimization (e.g., linear and mixed-integer programming), regression, classification, clustering, and time series forecasting—to solve real-world problems like scheduling, routing, and resource planning
• Proficiency in SQL and a solid understanding of data warehousing concepts and how to shape data for modeling and analysis
• Experience working with cloud platforms (especially AWS), and deploying models using native services such as Sagemaker, EC2, or Lambda
• Knowledge of big data technologies (e.g., Spark, Hadoop)
• Experience with MM specific data tooling - Terraform, dbt, and Snowflake
• Experience with real-time data processing tools (e.g., Kafka, Kinesis)
• Experience using container-based services (Docker, ECS, Kubernetes)

Benefits

• Competitive salaries
• Equity - Stock option plan on a standard 4 year vesting schedule with a 1 year cliff
• Unlimited paid vacation and flex time
• Health (mental & physical), dental, & HSA coverage across North America
• Remote work environment
• Flexible hours
• Tools
• Quarterly culture events