Role: Data Scientist

Location: Bay Area, CA (Hybrid)

Job type: Full Time

As a Forecasting Model Development Engineer, you will be responsible for designing, implementing, and evaluating advanced forecasting models to predict future trends and patterns in our industry. Leveraging your expertise in GCP, deep learning methodologies, and external data integration, you will collaborate with cross-functional teams to develop robust forecasting solutions that drive strategic decision-making and enhance business outcomes.

Key Responsibilities:

• Develop, implement and improve state-of-the-art forecasting models using deep learning techniques such as recurrent neural networks (RNNs), convolutional neural networks (CNNs), and transformers.
• Utilize Google Cloud Platform (GCP) tools and services for data storage, processing, and model deployment.
• Implement ML Workflows on GCP or an understanding DAG framework for workflows for model training, model evaluation and deployment.
• Conduct thorough data analysis to identify relevant external signals and incorporate them into forecasting models to improve accuracy and reliability.
• Collaborate with data engineers and data scientists to preprocess and transform data, ensuring compatibility with modeling requirements.
• Evaluate the performance of forecasting models using appropriate metrics and techniques and iterate on model design to optimize predictive accuracy.
• Work closely with stakeholders to understand business requirements and translate them into technical specifications for forecasting model development.
• Stay abreast of the latest advancements in deep learning, machine learning, and cloud technologies, and incorporate relevant techniques and methodologies into model development processes.
• Document methodologies, algorithms, and findings in a clear and concise manner, and communicate results to both technical and non-technical audiences.
• Provide technical guidance and mentorship to junior team members, fostering a culture of continuous learning and innovation.

Qualifications:

• Bachelor’s degree in computer science, engineering, mathematics, or related field; advanced degree (e.g., Master’s or PhD) preferred.
• Proven experience (X years) developing and implementing forecasting models using deep learning techniques, with a focus on time series analysis.
• Hands-on experience with Google Cloud Platform (GCP) services such as BigQuery, Cloud Storage, Vertex AI, Workflows, and Dataflow.
• Proficiency in programming languages such as Python, TensorFlow, and/or PyTorch for model development and evaluation.
• Domain knowledge of Regression based models such as Linear Regression, Random Forest, XGBoost, etc.
• Experience with ensembling multiple machine learning models in production environments.
• Strong understanding of statistical methods, data analysis, and machine learning concepts.
• Experience working with large-scale datasets and distributed computing environments.
• Excellent communication and collaboration skills, with the ability to effectively interact with cross-functional teams and stakeholders.
• Demonstrated ability to work independently, prioritize tasks, and manage time efficiently in a fast-paced environment.

Job Type: Full-time

Pay: $120,920.05 - $140,968.23 per year

Benefits:

• 401(k)
• Dental insurance
• Health insurance

Schedule:

• 8 hour shift

Ability to Relocate:

• San Francisco, CA: Relocate before starting work (Required)

Work Location: On the road