• Manage the data science portfolio and develop advanced analytics roadmap which supports Client’s strategic priorities.
• Architect, develop and deploy AI/ML/DL solutions that can be integrated into business systems and/or applications to improve decisions and outcomes.
• Own execution and delivery of advanced analytic projects including demos/tooling for end-users; provide regular releases to validate systems and iterate to improve benefits.
• Partner with business units to understand and assess new data sources (unstructured, semi-structured and structured) to improve existing capabilities and trigger new analytic solutions.
• Work collaboratively with a diverse team of developers in an agile environment providing critical input to support data required for decision systems and modeling solutions.
• Manage 2-3 data scientists and provide necessary direction to accomplish tasks to support EDA, data engineering, modeling, QA and performance monitoring.
• Masters or PhD in a quantitative discipline (Computer Science, Mathematics, Statistics, ML/AI, Engineering, Econometrics or equivalent).
• 7-10 years experience and high proficiency in data acquisition and manipulation of large datasets using databases in multiple environments.
• 7-10 years experience and high proficiency in Big Data programming languages.
• High proficiency in the use of statistical packages.
• Advanced experience and deep fundamental knowledge of supervised, unsupervised, reinforcement learning, machine learning algorithms such as classifiers, cluster analysis, dimension reduction, regression, ANN, CNN, RNN, Gradient Boosting, Random Forests, Bayesian Inference, NLP/NLU, etc. predictive and optimization modeling.
• Proficiency in Python, Spark, and SQL.
• Experience with model explain ability and interpretability techniques.
• Experience with cloud-based platforms and big data technologies Hadoop, Apache Spark, MapReduce, S3.
• Experience with Tableau or equivalent data visualization tools.
• Strong organization and planning skills and results-oriented mindset (driving to deadlines, targets, project goals).
• Ability to articulate, translate and present value of AI/ML solutions to senior leaders (VP and higher) to solve problems.