Data Scientist

6 days ago


Pleasanton, California, United States Ursus Inc Full time

Ursus Inc is seeking a skilled Data Scientist to join our team in Pleasanton, CA. This is a contract-to-hire opportunity with an estimated hourly rate of $85-$95.

About the Role

This Data Scientist position plays a critical role in developing and implementing machine learning models and algorithms that drive actionable intelligence. The ideal candidate will collaborate with cross-functional teams to analyze complex data sets, design and develop machine learning models, and build scalable solutions.

You will be responsible for optimizing and maintaining graph databases, ensuring high performance and efficient data retrieval. Your expertise in graph analytics, machine learning, and related fields will enable you to make a significant impact on our products and solutions.

Main Responsibilities
  • Design, develop, and implement machine learning models and algorithms that leverage graph databases to solve complex business problems.
  • Analyze and interpret complex datasets to extract meaningful insights and patterns.
  • Collaborate with cross-functional teams to define project requirements and objectives.
  • Optimize and maintain graph databases, focusing on performance and data retrieval efficiency.
  • Ensure the quality and reliability of machine learning models through rigorous testing and validation.
  • Stay updated with the latest advancements in machine learning and graph databases and incorporate them into our products and solutions.
  • Provide mentorship and guidance to junior machine learning engineers.
  • Document and communicate research findings, methodologies, and results to internal and external stakeholders.
Requirements
  • A Ph.D. in Computer Science with expertise in Machine Learning, Graph Theory, and related fields.
  • At least 5 years of experience in designing and implementing machine learning models and algorithms, with a focus on graph analytics.
  • Expertise in graph databases, Neo4j preferred, and their query languages (e.g., Cypher).
  • Proficiency in programming languages such as Python or R, as well as machine learning frameworks like TensorFlow or PyTorch.
  • A strong understanding of statistical modeling and data analysis techniques.
  • Experience with big data processing frameworks (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS) is a plus.
  • Excellent problem-solving and analytical skills.
  • The ability to work on complex problems and deliver innovative solutions.
  • Excellent communication and collaboration skills.


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