Responsibilities

• Partner with product, engineering, and business teams to translate ambiguous problems into data science solutions
• Design, develop, and deploy statistical models and machine learning algorithms in production environments
• Perform exploratory data analysis (EDA) to uncover trends, patterns, and actionable insights
• Build and evaluate predictive, classification, clustering, and/or recommendation models for identity resolution and audience segmentation
• Analyze large, complex datasets to extract actionable intelligence and drive data-informed decision making
• Build and optimize data pipelines (ETL) to support machine learning models in production
• Define success metrics and measure model and business impact over time
• Communicate findings clearly to both technical and non-technical audiences
• Collaborate with data engineers on data pipelines, feature engineering, and scalable model deployment
• Mentor junior data scientists and contribute to data science best practices
• Influence data strategy, tooling, and model governance across teams

Requirements

• 5+ years of experience in data science, applied statistics, or machine learning
• Master’s or PhD in Computer Science, Physics, Mathematics or related quantitative field
• Strong proficiency in Python (e.g., pandas, NumPy, scikit-learn)
• Experience with SQL and working with large, complex datasets
• Solid understanding of statistics, probability, and experimental design
• Hands-on experience deploying models into production environments
• Ability to clearly explain complex analyses and results to diverse stakeholders

Knowledge And Skills

• Experience with cloud platforms (AWS, Azure, or GCP)
• Familiarity with big data technologies (Spark, EMR, Databricks, etc.)
• Experience with deep learning frameworks (TensorFlow, PyTorch)
• Background in A/B testing, causal inference, or experimentation platforms
• Exposure to MLOps practices (model versioning, monitoring, CI/CD)
• Experience with identity resolution, customer segmentation, or marketing analytics
• Prior experience mentoring or leading data science initiatives
• Knowledge of data privacy regulations (GDPR, CCPA) and experience handling PII data securely
• Understanding of privacy-preserving machine learning techniques and anonymization methods

Benefits

• Flexible Time Off and Paid Holidays
• Medical/Vision/Dental Insurance, Voluntary Life & AD&D Insurance, Short-Term & Long-Term Disability, Critical Illness & Accident Insurance
• 401(k) with employer matching
• Hybrid with flexible work schedule

Location: Kirkland, WA (First 6 months in-office; hybrid schedule available thereafter—typically remote on Mondays and Fridays, with Tuesday–Thursday in-office, subject to manager’s discretion).

Registered to do business and willing to consider fully remote candidates in the following states; California, Colorado, Florida, Georgia, Missouri, New York, Oregon, South Carolina, Tennessee, Texas, and Washington. Work Authorization: Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time. Equal Opportunity Employer: Deep Sync provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. Please Contact: Human Resources | hr@deepsync.com