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.
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 and Generative AI
Lead the design, development, and deployment of advanced predictive models, LLMs, and machine learning solutions.
Ensure the scalability, reliability, and performance of data science solutions, implementing MLOps, and LLMOps, best practices.
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.
