Data Scientist & Machine Learning Engineer (Bellevue, Denver or LA)

Identity Digital•Bellevue, WA

3d•Hybrid

About The Position

The Data & Analytics team builds and manages data systems, analyzes information to generate insights, and develops machine learning models to support automated decision-making. The Data Scientist & Machine Learning Engineer works across data science and machine learning engineering to derive insights for decision-making, apply modeling techniques to business problems, and deploy and manage models in production. This role reports to the Director of Business Intelligence. The position is hybrid and based in one of Identity Digital’s U.S. offices in Bellevue, Washington; Denver, Colorado; or El Segundo, California. Candidates should live near one of these locations or be willing to relocate. The full-time base salary range is $107,000–$139,000, with flexibility based on experience. The successful candidate may also be eligible for discretionary and/or nondiscretionary bonuses and long-term incentives. Compensation is influenced by qualifications, internal equity considerations, and location. U.S. team members and eligible family members receive subsidized medical, dental, and vision insurance, including company contributions to Health Savings Accounts. The company provides life and disability insurance and offers optional supplemental insurance plans. Employees may enroll in the 401(k) plan with up to a 5% match. Paid leave includes 15 vacation days per year, increasing to 20 days after one year; five sick days; 13 holidays; and parental leave of 20 weeks for birthing parents and 12 weeks for others. Tuition reimbursement is available for qualifying expenses. Benefits are subject to eligibility requirements and may vary by location.

Requirements

At least 3 years of experience developing, deploying, and monitoring production data or machine-learning pipelines.
Bachelor’s degree in Mathematics, Computer Science, Data Science, Engineering, or another quantitative field.
Deep technical knowledge in several of the following areas: anomaly detection, time-series analysis, structured and unstructured data processing, causal inference, reinforcement learning, embeddings and vector databases, large language models, and modern MLOps or LLMOps practices.
Professional development experience with tools and platforms such as Airflow, Argo Workflows, cloud data warehouses (BigQuery, Databricks, Snowflake), major cloud providers (AWS, GCP), Git, Kubernetes, MLFlow, Pandas, Polars, PyTorch, TensorFlow, SHAP, and AI/LLMs.
Strong programming proficiency in Python and SQL.
Exceptional problem-solving skills, including the ability to diagnose and resolve issues with limited or ambiguous information.
Strong analytical foundation, creative and strategic thinking, and a focus on measurable impact.
Collaborative communication skills and the ability to build working relationships in cross-functional environments.
Strong organization, time management, attention to detail, and execution discipline.
Ability to travel as needed.
Ability to work across time zones as needed as part of a global organization.
Reliable transportation to the workplace.
Ability to sit for prolonged periods while working at a desk and computer.
Ability to lift up to 15 pounds at times.

Nice To Haves

Advanced degree (Master’s or Ph.D.) in AI/ML.
Familiarity with Shell scripting.
Knowledge of the domain name industry or digital identity ecosystem.

Responsibilities

Translate complex business problems into data, modeling, and machine-learning solutions.
Collect, clean, transform, and validate data for analysis and model development.
Explore data to identify patterns, trends, anomalies, and actionable insights.
Design, train, evaluate, and refine predictive or optimization models.
Select appropriate features, algorithms, metrics, and validation strategies.
Build reproducible data and machine-learning pipelines.
Deploy models for batch or real-time inference.
Develop and maintain infrastructure for reliable model serving.
Monitor model performance, data quality, drift, latency, and operational health.
Communicate findings and collaborate with stakeholders, engineers, and domain experts.
Model and promote Identity Digital’s core values through day-to-day interactions, behaviors, and decision-making.
Perform other duties as assigned.

Benefits

Subsidized medical, dental, and vision insurance for U.S. team members and eligible family members.
Company contributions to Health Savings Accounts.
Company-paid life and disability insurance.
Optional employee-paid supplemental life, accidental death and dismemberment, critical illness, and accident insurance.
401(k) plan with up to a 5% company match.
15 days of paid vacation yearly, increasing to 20 days after one year.
Five days of paid sick leave.
13 paid holidays.
Paid parental leave: 20 weeks for birthing parents and 12 weeks for others.
Tuition reimbursement for qualifying expenses.
Eligibility requirements apply and benefits may vary by location.