Senior Data Scientist

USEReady helps enterprises apply AI and agentic intelligence to improve decisions, automate operations, and build smarter, more autonomous business systems. For more than a decade, we have built the foundations that make this possible by modernizing BI environments, migrating legacy platforms, improving data quality, and enabling governed, cloud-first architectures.

We work closely with technology leaders such as AWS, Elementum, Snowflake, Tableau, Databricks, and others to help organizations modernize analytics, strengthen governance, and deploy agentic automation with confidence. Headquartered in New York City with 450+ experts across the United States, Canada, India, and Singapore, we serve industries including financial services, healthcare, manufacturing, government, education, and retail.

Role Summary

The Senior Data Scientist will lead advanced analytics initiatives, leveraging AI/ML, Generative AI (GenAI), and Agentic AI to deliver decision intelligence solutions. This role involves designing solutions, collaborating with cross-functional teams, and mentoring junior data scientists.

Key Responsibilities

• Design and implement advanced machine learning , Gen-AI, and Agentic AI based solutions.
• Apply GenAI and Agentic AI techniques to enhance decision-making workflows.
• Collaborate with sales and presales teams to craft proactive solution pitches for clients.
• Drive innovation in MLOps practices for scalable model deployment and monitoring.
• Conduct research on emerging AI technologies and integrate them into solutions.
• Mentor junior team members and foster a culture of continuous learning.
• Ensure compliance with AI governance and ethical standards.
  

Required Qualifications

• Bachelors or Masters or Ph.D. in Data Science, Machine Learning, or related field.
• 6+ years of experience in data science and AI/ML model development.
• Expertise in NLP, deep learning, and advanced ML frameworks (TensorFlow, PyTorch).
• Hands-on experience with Generative AI and Agentic AI.
• Strong knowledge of cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Proficiency in Python and SQL; familiarity with MLOps tools (MLflow, Kubeflow) and LLMOps tools (LangSmith, LangFuse).
• Knowledge of Snowflake would be beneficial.

Core Competencies

• Strategic thinking and problem-solving.
• Excellent communication and stakeholder engagement skills.
• Ability to lead complex projects and deliver business impact.