Join us in shaping the future of data-driven decision-making. As a Lead Data Science and Modeling Specialist, you will have the opportunity to lead impactful projects, collaborate with diverse teams, and drive innovation in AI/ML solutions. Your expertise will help us unlock new insights and deliver exceptional value to our business partners.

 As a Vice President- Applied AI/ML Lead in our Data Science and Modeling team, you will have the opportunity to lead impactful projects, collaborate with diverse teams, and promote innovation in AI/ML solutions. Your expertise will help us unlock new insights and deliver exceptional value to our business partners. You will spearhead data science engagements from conception to deployment, collaborating with business, governance, and tech stakeholders to articulate clear business use cases and deliver high-quality machine learning models. Your role is pivotal in optimizing existing models, ensuring high-quality data input, and providing technical guidance to global team members.

Job Responsibilities:

Lead end-to-end data science projects, interfacing with various stakeholders.Develop and deploy high-quality machine learning models and services.Optimize and maintain AI/ML models for improved performance and accuracy.Conduct data analysis and preprocessing for model training.Manage project prioritization and lead technology meetings with stakeholders.Participate in code reviews and foster a culture of continuous improvement.Provide technical guidance and mentorship to global team members.

Required qualifications, capabilities, and skills:

M.S. degree in Statistics, Engineering, Computer Science, or Mathematics.7+ years of experience in developing statistical or machine learning models.5+ years of experience with AI, including reinforcement learning or optimization algorithms.Proficient in Java or Python programming.Deep knowledge of data structures, algorithms, machine learning, and statistics.Expertise in at least one area: NLP, Computer Vision, Ranking and Recommendation, or Time Series Analysis.Familiarity with machine learning frameworks like Scikit-Learn, TensorFlow, PyTorch, etc.Experience with LLM usage, integration, and custom model fine-tuning.Experience with ETL data pipelines and data warehousing.Proficiency in SQL and NoSQL platforms for data mining and analysis.Strong analytical and critical thinking skills and excellent communication skills and a team player.

Preferred qualifications, capabilities, and skills:

Experience with cloud computing platforms: Azure, Google Cloud, AWS.Knowledge of distributed system design, including microservices and messaging systems.