This job offer is no longer available
Data Scientist
US Tech Solutions
- Sunnyvale, California, United States
- Sunnyvale, California, United States
About
Lead the design, development, testing, and global deployment of large‑scale time‑series forecasting models (including regression models and state‑of‑the‑art time‑series specific models such as N‑BEAST, PatchTST) to support complex retail and e‑commerce hierarchies. Introduce causal modeling approaches to conduct impact analysis for future forecast. Continuously enhance forecasting strategies by incorporating advanced machine learning architectures, including RNNs (sequence modeling), CNNs (temporal feature extraction), and attention‑based mechanisms to improve accuracy, scalability, and robustness in time‑series forecasting. Advance causal modeling frameworks to quantify event impacts and integrate causal insights into forward‑looking forecasts. Build and maintain experimentation pipelines (A/B testing, quasi‑experiments, multi‑armed bandits) for evaluating causal impacts of interventions. Mentor junior scientists, review research and production code, and ensure reproducibility and scalability in pipelines. Collaborate with engineering to implement forecasting + optimization systems in production (Airflow, Astronomer, Spark/Ray). Act as technical lead on multiple projects, balancing research rigor with business delivery.
What you’ll bring
Strong foundation in Time Series Forecasting, Causal Inference, Statistical Analysis, and advanced Machine Learning methods. Hands‑on experience with a wide range of ML techniques, with a deep understanding of their advantages and limitations across different scenarios. Ability to integrate statistical expertise with machine learning methods to maximize the value and interpretability of ML solutions. Proficiency in Python, SQL, PyTorch, Spark/Ray, and stats/econometrics libraries. Experience deploying ML systems at scale on cloud platforms (GCP/Azure).
Great to have
Publications and open‑source contributions spanning the full spectrum of modern Machine Learning, from statistical learning (e.g., Bayesian modeling, causal inference, high‑dimensional statistical methods) to deep learning (e.g., convolutional and transformer‑based architectures) and reinforcement learning (e.g., dynamic programming, policy gradient methods). Exposure to ML observability: drift detection, retraining triggers, and causality‑informed monitoring. Background in retail, e‑commerce, or operations analytics.
About US Tech Solutions US Tech Solutions is a global staff augmentation firm providing a wide range of talent on‑demand and total workforce solutions. To know more about US Tech Solutions, please visit www.ustechsolutions.com. US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Recruiter Details Recruiter’s email id: ajeetk@ustechsolutionsinc.com JobDiva ID :: JobDiva # 25-53396 #J-18808-Ljbffr
Languages
- English
Notice for Users
This job was posted by one of our partners. You can view the original job source here.