Senior BI Data Researcher

Accountabilities

• • Investigate heterogeneous data management techniques and polystore architectures, applying AI and machine learning to challenges such as data quality, data profiling, data integration, and schema matching.
  • Research and develop scalable tools and frameworks for machine learning models and data science algorithms across multiple data domains, including tabular, time-series, text, audio, and video data.
  • Design and develop distributed data processing architectures that leverage edge computing to support innovative use cases such as predictive routing, data-driven experiences, and adaptive environments.
  • Explore advanced approaches to data management, including storage, caching, query processing, query optimization, resource management, security, and privacy.
  • Conduct research into data analytics, information extraction, metadata management, search and discovery, data visualization, natural language processing, and related areas.
  • Collaborate with peer research teams to identify and pursue opportunities involving applied AI and machine learning, including emerging applications involving audio and video data.
  • Translate research findings into practical tools, frameworks, prototypes, and scalable data solutions.
  • Contribute to technical documentation, project planning, version control, and collaborative development practices.

  Requirements

  • PhD in Computer Science or a closely related technical field.
  • Strong academic or professional background in relational databases, big data systems, and data analytics systems.
  • Deep expertise in data management, data cleaning, distributed systems, database storage engines, query processing, and query optimization.
  • Demonstrated experience applying data science and machine learning techniques to real-world or research problems.
  • Hands-on experience developing machine learning models and data science algorithms across diverse data types, including tabular, time-series, text, audio, and video.
  • Strong understanding of scalable data processing architectures and distributed computing concepts.
  • Knowledge of data integration, schema matching, data quality, data profiling, metadata, or related data management challenges.
  • Ability to investigate complex technical problems independently and translate research concepts into practical implementations.
  • Familiarity with Git and project management tools such as JIRA.
  • Strong analytical, research, technical communication, and cross-functional collaboration skills.
  • Comfortable working independently in a fully remote environment while collaborating with distributed research and engineering teams.

  Benefits

  • Annual salary of $140,000–$160,000.
  • Full-time, direct-hire employment.
  • 100% remote work within the United States.
  • Opportunity to work on advanced problems spanning big data, distributed systems, AI, machine learning, and data science.
  • Exposure to research-driven projects involving heterogeneous data, edge computing, and emerging technologies.
  • Collaborative environment with opportunities to work alongside peer research teams.
  • Opportunity to develop scalable frameworks and solutions with potential applications across multiple data domains.