About this role
KEY RESPONSIBILITIES
Efficient & Reliable Independent Contributor
• Independently design and implement complex data science projects, from initial concept through final deployment.
• Solve critical business problems with minimal oversight, ensuring the delivery of high-quality, impactful solutions.
• Proactively identify and address potential issues or opportunities for improvement in existing models and processes.
• Design scalable data and knowledge pipelines (chunking, indexing, vector stores) optimized for GenAI and enterprise use cases.
Leadership and Mentorship
• Mentor and provide technical guidance to junior data scientists and team members.
• Foster a culture of continuous learning and improvement within the team.
Advanced Model Development
• Lead the design, development, and deployment of advanced predictive models and machine learning solutions.
• Ensure the scalability, reliability, and performance of data science solutions, implementing MLOps best practices.
• Architect GenAI solutions (RAG, agents, tool‑calling, multimodal systems) aligned to business workflows and constraints.
• Define robust GenAI evaluation frameworks covering quality, safety, cost, latency, and business impact.
Strategic Collaboration
• Collaborate with business stakeholders to identify and prioritize opportunities for leveraging data to drive strategic business solutions.
• Communicate complex analytical concepts and findings to non-technical stakeholders, influencing decision-making at the highest levels.
Research and Innovation
• Conduct in-depth research and analysis to develop innovative data science solutions that address complex business problems.
• Drive the adoption of cutting-edge techniques and best practices in data science, machine learning, and AI across the organization.
Data Pipeline Management
• Oversee the end-to-end data pipeline, from data collection and processing to model deployment, monitoring, and optimization.
• Implement robust validation and monitoring processes to ensure data quality and integrity.
Thought Leadership
• Stay abreast of the latest trends and advancements in the field of data science.
• Actively contribute to the organization's thought leadership through publications, presentations, and participation in industry events.
QUALIFICATIONS
• Bachelor’s, Master’s or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• 8+ years of experience in data science or a related field, with a proven track record of leading and delivering high-impact projects.
• Deep expertise in advanced machine learning techniques, statistical modeling, and AI.
• Strong proficiency in programming languages such as Python, with extensive experience in machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
• Advanced skills in SQL and experience with big data technologies.
• Proven experience with MLOps practices and tools for model deployment, monitoring, and optimization.
• Exceptional problem-solving skills and a strategic mindset, with the ability to tackle complex data challenges.
• Strong leadership and mentorship abilities, with experience guiding and developing junior team members.
• Outstanding communication skills, both written and verbal, with the ability to effectively convey complex technical concepts to diverse audiences.