AI-First Data Scientist

Jobgether

20h

About The Position

We are seeking a highly skilled AI-First Data Scientist to design and deploy production-ready machine learning solutions that directly influence strategic business decisions. This role combines deep expertise in causal inference, MLOps, and cloud-based ML platforms to build models that not only inform but automate and optimize operations across multiple business units. You will work closely with senior operators and executives, translating ambiguous problems into measurable, scalable ML frameworks. The position offers the opportunity to take end-to-end ownership of high-impact projects, from experimentation and model design to production deployment and ongoing monitoring. Collaboration with engineering and analytics teams ensures robust pipelines, reproducibility, and continuous improvement. This role is ideal for data scientists who thrive in fast-moving, AI-driven environments and want to embed intelligence into the core of business operations.

Requirements

• 5+ years of experience in applied data science or machine learning engineering with production deployment of models.
• Master’s or PhD in Data Science, Computer Science, Statistics, Economics, or related quantitative field.
• Expertise in causal inference frameworks, A/B testing, uplift modeling, and other counterfactual methods.
• Strong proficiency in Python or R, SQL, Jupyter, Git, and cloud ML platforms (AWS Sagemaker preferred).
• Experience with MLOps tools for experiment tracking, model registry, and automated deployment.
• Ability to handle large datasets, distributed computing frameworks, and advanced data engineering best practices.
• Demonstrated track record of taking cross-functional, ambiguous problems from exploration to deployed ML solutions with clear success metrics.

Responsibilities

• Develop and deploy end-to-end ML pipelines using modern MLOps practices and cloud-native platforms such as AWS Sagemaker.
• Conduct causal inference analyses, including Double Machine Learning (DML), uplift modeling, and quasi-experimental design, to guide high-stakes business decisions.
• Build, train, and optimize predictive and prescriptive models for pricing, inventory, marketing attribution, personalization, and other business applications.
• Integrate models into production systems, monitor performance, diagnose drift and data quality issues, and ensure reproducibility.
• Translate ambiguous business challenges into structured ML frameworks that deliver measurable ROI.
• Partner with engineering and analytics teams to improve data pipelines and maintain version-controlled, CI/CD-enabled ML workflows.
• Continuously research and apply emerging AI techniques, including generative AI, automated feature engineering, and reinforcement learning.

Benefits

• Competitive salary and performance-based incentives.
• Flexible paid time off and comprehensive leave policies.
• Health, dental, and vision coverage.
• 401(k) with company match.
• Direct mentorship and collaboration with senior business and technical leaders.
• Opportunity to work with cutting-edge AI tools and methodologies.
• Career growth and accelerated leadership opportunities across multiple business units.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level