TL;DR

Lead Data Scientist (AI): Developing and deploying advanced data products and machine learning solutions to drive strategic decision-making and uncover deep insights from telemetry data. With an accent on ML model design, predictive algorithms, and MLOps best practices. Focus on solving complex observability problems, architecting scalable data science frameworks, and mentoring junior data scientists.

Location: Remote (US-based due to listed cities, benefits, and visa sponsorship not available)

Salary: $163,000 – $204,000 USD

Company

%hirify_global% is a product company building an intelligent observability platform that empowers companies to thrive in an AI-first world.

What you will do

Lead the design, development, and deployment of advanced ML models and predictive algorithms for business problems like churn prediction and user segmentation.
Serve as a technical subject matter expert, guiding the team on best practices in statistical analysis and experimentation design.
Partner with Product Managers and Engineers to translate business questions into rigorous data science projects.
Drive the adoption of MLOps best practices, ensuring models are scalable, reproducible, and effectively monitored.
Perform deep-dive analyses on user behavior and product performance to identify optimization and growth opportunities.
Mentor and coach other data scientists, fostering a culture of continuous technical learning and innovation.

Requirements

7+ years of experience in Data Science, Statistics, or a related field, with a proven track record of delivering high-impact machine learning solutions.
Expert-level proficiency in Python for data manipulation, statistical analysis, and model development (pandas, scikit-learn, numpy).
Advanced knowledge of SQL for complex data querying and performance optimization.
Strong hands-on experience with supervised learning (Regression, Random Forests, XGBoost), unsupervised learning (Clustering, Dimensionality Reduction), and time series forecasting (ARIMA, Prophet).
Experience with dbt for data transformation and maintaining clean, reliable data pipelines.
Demonstrated ability to deploy models into production environments and familiarity with MLOps concepts.
Familiarity with software engineering practices (CI/CD, version control with Git, Jira).
Strong communication skills, with the ability to influence stakeholders and explain technical concepts to business audiences.
Expertise in developing or integrating GenAI models or AI agents into product and analytical workflows.
Visa sponsorship is not available for this position.

Nice to have

Experience with cloud-based machine learning platforms, specifically AWS SageMaker.
Background in observability.
Advanced degree (Master’s or PhD) in a quantitative discipline.
Proficiency in data visualization tools (e.g., Tableau, Looker) to democratize insights.

Culture & Benefits

Flexible workforce model allowing fully office-based, fully remote, or hybrid work.
Comprehensive benefits including healthcare, dental, vision, parental leave, and mental health support.
401(k) plan and match.
Flex time-off, 11 paid holidays, and volunteer time-off.
Commitment to fostering a diverse, welcoming, and inclusive environment.
Other competitive benefits designed to improve employees' lives.

Hiring process

Identity and eligibility to work verification.
Completion of a criminal background check.