Staff Data Scientist

This is a fully remote position, open to applicants in California.

📋 Description

• Take ownership of the entire machine learning lifecycle—from problem identification and data analysis to modeling, deployment, and ongoing monitoring—for critical mission initiatives.

• Develop and implement sophisticated ML and statistical models that enhance product performance, operational efficiency, or customer insights.

• Work collaboratively with engineers, product managers, and business stakeholders to establish project scope, success metrics, and integration strategies.

• Provide guidance on architectural choices, set modeling standards, and advocate for best practices regarding experimentation, validation, and productionization.

• Mentor fellow data scientists and elevate the technical standards through design reviews, constructive feedback, and sharing of domain knowledge.

• Actively seek out opportunities where data science can provide business value and lead cross-functional initiatives to advance those opportunities.

• Utilize cutting-edge AI tools to refine your development workflow, boost productivity, and help innovate new methods of building—fostering a culture of innovation and efficiency within the team.

⛳️ Requirements

• Over 5 years of experience in data science with a demonstrated history of delivering production ML systems that produce measurable results.

• Extensive knowledge of statistical modeling, machine learning (e.g., tree-based models, time series analysis, deep learning), and model assessment.

• Experience handling real-world product data at scale and converting ambiguous challenges into clearly defined ML solutions.

• Familiarity with distributed data processing and training, real-time inference, and ML Ops frameworks.

• Previous experience in mentoring data scientists or serving as a technical lead.

• Experience in leading experimentation (e.g., A/B testing), causal inference, and real-time decision-making systems.

• Proficient in Python and SQL, with hands-on experience in ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).

• Solid understanding of software engineering principles including modular design, version control, testing, and CI/CD practices.

• Practical experience with cloud platforms (preferably AWS), including tools such as SageMaker, Athena, Glue, DynamoDB, and Bedrock.

• Exceptional communication skills with the ability to influence both technical and non-technical stakeholders.

• Strong business insight with the capability to align technical solutions with organizational objectives.

🏝️ Benefits

• Health insurance

• Retirement plans

• Paid time off

• Flexible work arrangements

• Professional development

• Bonuses

• Stock options

• Equipment allowances

• Wellness programs