CAI
Join Our Team as a Lead Data Scientist!
Are you ready to take your career to the next level? At CAI, we're a forward-thinking technology services firm committed to innovation for our clients, colleagues, and communities. With over 8,500 associates globally and a revenue of $1 billion+, we have a rich history of excellence spanning over 40 years.
Your Mission:
As a Lead Data Scientist, you will play a vital role in developing and implementing cutting-edge demand forecasting models across thousands of SKUs. You'll manage the entire lifecycle of modeling, from data exploration to automated updates and performance evaluations, ensuring our solutions deliver measurable impact.
Key Responsibilities:
Advanced ML Algorithms:
Design and refine both supervised and unsupervised models, employing techniques like hyperparameter optimization and model interpretability. Data Analysis & Feature Engineering:
Conduct in-depth exploratory data analysis and create predictive features from varied data structures, ensuring high data quality. Time Series Forecasting:
Construct and optimize forecasts using both traditional and advanced deep learning techniques, while continually assessing their accuracy. MLOps & Model Lifecycle:
Implement robust model tracking and CI/CD pipelines, monitoring performance and making adjustments as necessary. Statistical Analysis & Experimentation:
Design and evaluate experiments, translating data insights into tangible business recommendations. Collaboration & Leadership:
Be a key translator of business needs into data-driven solutions, mentoring junior team members and sharing insights with stakeholders. Qualifications: Master’s degree in Statistics, Applied Mathematics, Computer Science, or a related field. Over 5 years of experience with machine learning models in production. Proficient in Python, SQL, and version control systems. Experience in delivering demand forecasting or time series solutions effectively. Familiar with MLOps tools for model management and deployment. Solid understanding of statistical inference and experimental design. Background in supply chain, retail, or manufacturing with detailed SKU data. Knowledge of distributed data frameworks and cloud data solutions. Expertise in deep learning frameworks and data visualization tools. This position can be performed in a hybrid work environment, allowing you flexibility in your schedule. If you're ready to make a difference with your skills and grow within our vibrant team, we encourage you to apply today! Please reach out for reasonable accommodations during the application process if needed.
Design and refine both supervised and unsupervised models, employing techniques like hyperparameter optimization and model interpretability. Data Analysis & Feature Engineering:
Conduct in-depth exploratory data analysis and create predictive features from varied data structures, ensuring high data quality. Time Series Forecasting:
Construct and optimize forecasts using both traditional and advanced deep learning techniques, while continually assessing their accuracy. MLOps & Model Lifecycle:
Implement robust model tracking and CI/CD pipelines, monitoring performance and making adjustments as necessary. Statistical Analysis & Experimentation:
Design and evaluate experiments, translating data insights into tangible business recommendations. Collaboration & Leadership:
Be a key translator of business needs into data-driven solutions, mentoring junior team members and sharing insights with stakeholders. Qualifications: Master’s degree in Statistics, Applied Mathematics, Computer Science, or a related field. Over 5 years of experience with machine learning models in production. Proficient in Python, SQL, and version control systems. Experience in delivering demand forecasting or time series solutions effectively. Familiar with MLOps tools for model management and deployment. Solid understanding of statistical inference and experimental design. Background in supply chain, retail, or manufacturing with detailed SKU data. Knowledge of distributed data frameworks and cloud data solutions. Expertise in deep learning frameworks and data visualization tools. This position can be performed in a hybrid work environment, allowing you flexibility in your schedule. If you're ready to make a difference with your skills and grow within our vibrant team, we encourage you to apply today! Please reach out for reasonable accommodations during the application process if needed.