Sr Data Scientist

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.