Senior AI Scientist

About This Role

This role involves building and deploying advanced AI/ML algorithms to optimize operational efficiency, predict demand, and enhance decision-making within customer success networks for a leading financial software company.

Responsibilities

• Perform hands-on data analysis and modeling with massive datasets, including discovering data sources and building ETL pipelines
• Apply data mining, NLP, and machine learning (supervised and unsupervised) to improve relevance and personalization
• Design and implement algorithms for complex operational problems, including demand forecasting, capacity planning, and resource scheduling
• Design A/B tests, analyze results, draw statistical conclusions, and communicate actionable insights to peers and leadership
• Create and refine features from underlying data, developing subject matter expertise to build intuition on model performance
• Explore new design shifts and technology trends such as GenAI or Reinforcement Learning to solve customer problems or improve operational efficiency

Requirements

• MS or PhD in a quantitative field (Computer Science, Statistics, Applied Math, Operations Research, Physics, etc.)
• 4+ years of industry experience with Data Science/AI (or 2+ years with a PhD)
• Strong proficiency in Python or R, with expertise in modern analytical libraries (e.g., scikit-learn, pandas, numpy)
• Proficiency in SQL and experience working with large-scale data ecosystems (Hive, SparkSQL, etc.)
• Comfortable working in a Linux environment
• Solid foundation in data mining and statistical modeling techniques: clustering, classification, regression, decision trees, neural nets, SVMs, and anomaly detection
• Demonstrated ability to explain complex technical issues and trade-offs to both technical and non-technical audiences
• Expertise in applied Time Series Forecasting (ARIMA, Prophet, Neural methods) with ability to handle sparsity, hierarchical constraints, and recurrent events

Qualifications

• MS or PhD in a quantitative field (Computer Science, Statistics, Applied Math, Operations Research, Physics, etc.)
• 4+ years of industry experience with Data Science/AI (or 2+ years with a PhD)

Nice to Have

• Interest or experience in Reinforcement Learning (RL)
• Experience applying Deep Learning techniques to memory-constrained problems or complex pattern recognition
• Background in Workforce Management (WFM), Supply Chain, Logistics, or Gig-Economy dynamic pricing/matching

Skills

* Required skills

Benefits