Senior Data Engineer

• Develop scalable time series forecasting systems leveraging global models like Temporal Fusion Transformers, N-BEATS, and PATCHTST, enabling robust forecasting across thousands of retail and e-commerce time series.
• Foundational Knowledge on advanced regression.
• Apply generative AI to synthesize time series data, enhance model training pipelines, and build intelligent NLP-based assistants for analytics enablement.
• Design and train large-scale neural networks for time series, anomaly detection, and causal inference, with deployment via automated batch pipelines
• Build and maintain production-ready applications on cloud platforms, integrated with internal systems to deliver insights at scale. Collaborate with cross-functional teams to define objectives, formulate hypotheses, and deploy models that directly influence decision-making.

• Strong foundation in time series forecasting, deep learning, and optimization theory, with a focus on sequence modeling and attention-based architectures.
• Experience in training and deploying transformer-based neural networks (e.g., TFT, LSTM, GPT variants) for real-world business applications.
• Proficient in Python, SQL, and hands-on with PyTorch, TensorFlow/Keras, Scikit-learn, and statsmodels. Demonstrated ability to work on GPU-based model training pipelines, and exposure to managing experimentation at scale.

Nice to Have Skills & Experience

• Enterprise level experience preferred
• Deep Learning
• Agentic
• Gen AI
• Language Models

Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.