Senior Data Scientist
hace 1 semana
Tiger Analytics is looking for an experienced Senior Data Scientist to join our team. As a leading advanced analytics consulting firm, we help Fortune 500 companies generate valuable insights from their data. With our deep expertise in Data Science, Machine Learning, and AI, we deliver innovative solutions to complex business problems. As a Senior Data Scientist at Tiger Analytics, you will have the opportunity to work on cutting-edge projects, collaborate with cross-functional teams, and drive business value through advanced analytics.
Key Responsibilities: Work on the latest applications of data science to solve business problems. Effectively communicate the analytics approach and how it will meet and address objectives to business partners. Lead analytic approaches; integrate solutions collaboratively into applications and tools with data engineers, business leads, analysts, and developers. Create repeatable, interpretable, dynamic, and scalable models seamlessly incorporated into analytic data products. Collaborate, coach, and learn with a growing team of experienced Data Scientists. Stay connected with external sources of ideas through conferences and community engagements. Support demands from regulators, investor relations, etc., to develop innovative solutions to meet objectives utilizing cutting-edge techniques and tools. Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. Minimum of 5 years of experience in Data Science and Machine Learning. Solid understanding of machine learning algorithms and statistical analysis. 2-3 years of Model building and Enterprise-level deployement experience. Proficiency in Python and PySpark programming languages commonly used in Data Science. Experience with cloud platforms such as Azure and AWS is a plus. Ability to preprocess and clean large datasets for analysis. Strong problem-solving skills and ability to think analytically. Excellent communication and presentation skills. Ability to work effectively in cross-functional teams and manage multiple projects simultaneously.
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