Senior Data Scientist

Overview

Req number: R5797

Employment type: Full time

Worksite flexibility: Remote Who we are
CAI is a global technology services firm with over 8,500 associates worldwide and a yearly revenue of $1 billion+. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients, colleagues, and communities. As a privately held company, we have the freedom and focus to do what is right—whatever it takes. Our tailor-made solutions create lasting results across the public and commercial sectors, and we are trailblazers in bringing neurodiversity to the enterprise.

Job Summary We’re searching for an experienced Senior Data Scientist who excels at statistical analysis, feature engineering, and end to end machine learning operations. Your primary mission will be to build and productionize demand forecasting models across thousands of SKUs, while owning the full model lifecycle—from data discovery through automated re training and performance monitoring. This is a Full-time and Hybrid position.

Job Description
What You’ll Do
Advanced ML Algorithms: Design, train, and evaluate supervised & unsupervised models (regression, classification, clustering, uplift).
Apply automated hyper‑parameter optimization (Optuna, HyperOpt) and interpretability techniques (SHAP, LIME).
Data Analysis & Feature Engineering: • Perform deep exploratory data analysis (EDA) to uncover patterns & anomalies.
Engineer predictive features from structured, semi‑structured, and unstructured data; manage feature stores (Feast).
Ensure data quality through rigorous validation and automated checks.
Time‑Series Forecasting (Demand): • Build hierarchical, intermittent, and multi‑seasonal forecasts for thousands of SKUs.
Implement traditional (ARIMA, ETS, Prophet) and deep‑learning (RNN/LSTM, Temporal‑Fusion Transformer) approaches.
Reconcile forecasts across product/category hierarchies; quantify accuracy (MAPE, WAPE) and bias.
MLOps & Model Lifecycle: • Establish model tracking & registry (MLflow, SageMaker Model Registry).
Develop CI/CD pipelines for automated retraining, validation, and deployment (Airflow, Kubeflow, GitHub Actions).
Monitor data & concept drift; trigger re‑tuning or rollback as needed.
Statistical Analysis & Experimentation: • Design and analyze A/B tests, causal inference studies, and Bayesian experiments.
Provide statistically‑grounded insights and recommendations to stakeholders.
Collaboration & Leadership: Translate business objectives into data‑driven solutions; present findings to exec & non‑tech audiences.
Mentor junior data scientists, review code/notebooks, and champion best practices.

What You'll Need
M.S. in Statistics (preferred) or related field such as Applied Mathematics, Computer Science, Data Science.
5+ years building and deploying ML models in production.
Expert‑level proficiency in Python (Pandas, NumPy, SciPy, scikit‑learn), SQL, and Git.
Demonstrated success delivering large‑scale demand‑forecasting or time‑series solutions.
Hands‑on experience with MLOps tools (MLflow, Kubeflow, SageMaker, Airflow) for model tracking and automated retraining.
Solid grounding in statistical inference, hypothesis testing, and experimental design.
Experience in supply‑chain, retail, or manufacturing domains with high‑granularity SKU data.
Familiarity with distributed data frameworks (Spark, Dask) and cloud data warehouses (Big Query, Snowflake).
Knowledge of deep‑learning libraries (PyTorch, TensorFlow) and probabilistic programming (PyMC, Stan).
Strong data‑visualization skills (Plotly, Dash, Tableau) for storytelling and insight communication.

Physical Demands
This role involves mostly sedentary work, with occasional movement around the office to attend meetings, etc.
Ability to perform repetitive tasks on a computer, using a mouse, keyboard, and monitor.

Reasonable accommodation statement
If you require a reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employment selection process, please direct your inquiries to application.accommodations@cai.io or (888) 824 – 8111.