Data Scientist

US Tech Solutions; Sunnyvale (CA); On-site; USD 140,000 - 250,000; Full time

Job summary

A global staff augmentation firm is seeking a Team Lead - IT Recruitment in Sunnyvale, California. This role involves leading the design and deployment of advanced forecasting models and collaborating with finance teams. The ideal candidate will have a strong foundation in machine learning, statistical analysis, and causal inference. Responsibilities include mentoring junior scientists and implementing systems in production, enhancing strategies, and advancing causal modeling frameworks. Competitive pay range from $140,000 to $250,000 per year.

Qualifications

• 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.
• Ability to integrate statistical expertise with machine learning methods.

Responsibilities

• Lead the design, development, testing, and deployment of large-scale time-series forecasting models.
• Continuously enhance forecasting strategies using advanced machine learning architectures.
• Build and maintain experimentation pipelines for evaluating causal impacts of interventions.

Skills

Time Series Forecasting

Causal Inference

Statistical Analysis

Machine Learning

Python

SQL

PyTorch

Spark/Ray

Job description

This range is provided by US Tech Solutions. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base Pay Range

$140.00/yr - $250.00/yr

Direct message the job poster from US Tech Solutions

Team Lead - IT Recruitment at US Tech Solutions with expertise in Recruitment and MSP clients

Opportunity to work on financial data for complex problems and challenges. Utilize LLMs/GenAI systems and architectures to build and deploy state-of-the-art GenAI systems.

Our team collaborates closely with Finance teams to enhance financial planning and strategic decision‑making through cutting‑edge data‑driven solutions. We specialize in initiatives that provide actionable insights into trends and patterns and leverage Generative AI (GenAI) to produce concise, insightful summaries that empower decision‑makers. By integrating these innovative approaches, we strive to drive efficiency, accuracy, and impactful outcomes in financial operations.

About Team

Our team works closely with our US stores and eCommerce business to better serve customers by empowering team members, stores, and merchants with technological innovation. From groceries and entertainment to sporting goods and crafts, our extensive selection that customers value whether they shop online through one of our mobile apps or in‑store. Focus areas include customers, stores and employees, in‑store service, merchant tools, merchant data science, and search and personalization.

What you’ll do

• 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: [e-mail]

JobDiva ID :: JobDiva # 25-53396