Job Description

As a Data Scientist, you will use your expertise in Data Science/Machine Learning to tackle exciting problems such as: addressing fairness and bias in recommendation systems, using reinforcement learning to optimize long-term engagement metrics, using transformer models in recommendation systems, building multimodal models, etc.


Key Responsibilities:

  • Collaborate with business partners to develop innovative solutions to meet objectives utilizing cutting edge techniques and tools.
  • Effectively communicate the analytics approach and how it will meet and address objectives to business partners.
  • Advocate and educate on the value of data-driven decision making; focus on the “how and why” of solutioning.
  • 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 that are seamlessly incorporated into analytic data products.
  • Use data science and machine learning methods to bootstrap new functionalities.
  • Handle competing requests from a range of data customers.
  • Tackle complex problems that arise in production and find customer-centric solutions.
  • Engineer features by using your business acumen to find new ways to combine disparate internal and external data sources.
  • Share your passion for Data Science with the broader enterprise community; identify and develop long-term processes, frameworks, tools, methods and standards.
  • Collaborate, coach, and learn with a growing team of experienced Data Scientists.
  • Stay connected with external sources of ideas through conferences and community engagements.

Requirements:

  • Bachelors Degree in Data Science, Computer Science, Applied Mathematics, or Statistics
  • 5+ years of Data Science and Machine Learning experience required
  • Proficiency in Python or R. Ability to write complex SQL queries
  • Proficiency with Machine Learning concepts and modeling techniques to solve problems such as clustering, classification, regression, anomaly detection, simulation and optimization problems on large scale data sets
  • Experience with AWS is a plus
  • Ability to implement ML best practices for the entire Data Science lifecycle
  • Ability to apply various analytical models to business use cases (NLP, Supervised, Un-Supervised, Neural Nets, etc.)
  • Exceptional communication and collaboration skills to understand business partner needs and deliver solutions
  • Bias for action, with the ability to deliver outstanding results through task prioritization and time management
  • Experience with data visualization tools — Tableau, Power BI, etc. preferred

Compensation ranges between: $85K - $120K

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Flexible Working Policies

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