Data Science Principal

Lead a team of data scientists, providing mentorship and guidance on daily tasks, fostering professional development and capability growth. Oversee the implementation of Continuous Integration/Continuous Deployment (CI/CD) pipelines, ensuring deliverables meet project milestones and quality standards. Apply advanced machine learning, forecasting, and statistical analysis techniques to drive experimentation and innovation on data science projects. Lead the experimentation and implementation of new data science techniques for projects, ensuring alignment with internal and external customer objectives. Communicate project status, methodologies, and results to both technical teams and business stakeholders, translating complex data insights into actionable strategies. Facilitate data science team discussions, providing technical expertise on current methods and guiding decision-making for optimal outcomes. Contribute to strategic data science initiatives, influencing the direction of key projects and aligning team efforts with broader business goals. Encourage collaboration across teams and functions to ensure seamless integration of data science solutions into business processes and technology platforms. Experience Experience in people and/or project management activities. Utilized multiple data science methodologies. Qualifications Degree in Data Science, Computer Science, Engineering, Science, Information Systems and/or equivalent formal training plus work experienceBS & 7+ years of work experience MS & 6+ years of work experience Excellent communication skills.7+ years of work experience in a data science role Familiarity with Data Science software & platforms (e.g. Databricks) Software development experience Research and new algorithm development experience Skills and knowledge Demonstrable experience of machine learning techniques and algorithms Experience with statistical techniques and CRISP-DM lifecycle. Production ML Experience: Deployed models that serve real users, ability of scale to million users without incurring technical debt.Strong programming skills in Python and familiarity with ML libraries and frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar.MLOPS experience with tools such as Drift, Decay, A/B Testing. Integration and Differential testing, python package building, code version etc. Experience with data pipeline creation and working with structured and unstructured data. Familiarity with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes) preferred. Excellent problem-solving skills combined with the ability to communicate complex technical concepts to non-technical stakeholders.Ability to mentor team of Data Scientists, Machine Learning Engineers and Data Engineers with strategy making capability.