Senior Data Scientist (AI/ML)

About the job Senior Data Scientist (AI/ML) Our client is looking for an experienced individual contributor with expertise in production-ready AI/ML solutions. In the role of Senior Data Scientist, you will be part of a team of Data Scientists, led by a Lead Data Scientist, focused on developing advanced data science solutions that utilize machine learning and artificial intelligence to drive innovation across various business lines and products. Collaboration with cross-functional teams in Data Science, Data Engineering, and Business groups is a key aspect of this role. We are seeking candidates with a strong technical foundation, coding proficiency, attention to detail, and a passion for analytical thinking and problem-solving. Qualifications: A PhD with 2 years of experience or a Master's degree with 4 years of experience in fields such as Statistics, Computer Science, Engineering, Applied mathematics, or related disciplines. A minimum of 3 years of hands-on experience in ML modeling and development. Strong understanding of data analysis and statistical modeling. Knowledge of various machine learning techniques (clustering, decision trees, bagging/boosting, artificial neural networks, etc.) and their real-world applications and limitations. Proven track record in experimental design and execution. Hands-on experience with data wrangling, including fuzzy matching and regular expressions, distributed computing, and parallelism in ML solutions. Proficient programming skills in Python. Solid background in algorithms and familiarity with a range of ML models. Excellent communication skills and the ability to collaborate effectively across different teams, from leadership to hands-on levels. Outstanding analytical and problem-solving abilities with meticulous attention to detail. Demonstrated leadership in providing technical guidance and mentoring to data scientists, along with effective management skills for monitoring and tracking performance to ensure success within the organization. Locations: Northeastern USA - Hybrid/Remote (2-3 days per/week)