Role Purpose

Baker McKenzie is investing in a new capability: uniting data science, internal and external data, machine learning and legal domain expertise to create new value for our clients, our firm and our communities. At the centre of the firm’s Reinvent programme, this is at the cutting edge of innovation in the legal services industry. You will be there from the beginning, part of the new BakerML team, working on pioneering projects to deliver machine learning enabled legal judgment.

To coordinate, consolidate and oversee mitigation of all data quality issues in the organization. 


The BakerML team is a specialist, multi-disciplinary group of experts from across multiple functions in the Firm. The BakerML team will work closely with leading AI technology company, SparkBeyond. Under the leadership of Chief Innovation Officer, Ben Allgrove, the team will leverage SparkBeyond’s AI-powered advanced analytics and augmented research platforms on a series of projects, exploring new ways to apply machine learning to transform the legal industry and address key societal problems.


Main Responsibilities

  •  Design, Create, Structure and Lead the Enterprise Data Quality Function
  • Develop a deep understanding of Firm's data sources, data maintenance processes and data models.
  • Consolidate all data quality operations under a single umbrella and service line.
  • Field data quality certification and improvement requests from stakeholders
  • Develop symbiotic relationships with firm's data custodians and process owners
  • Define Enterprise Data Quality Standards and Guidelines
  • Create standard Data Quality checklists that can be used to measure data quality gaps and configure data quality measurement tools/technologies
  • Train, lead and support Data Quality engineers to help identify, quantify and report on data quality issues
  • Train, lead and support a group of Data Guardians to help data custodians mitigate data quality issues at scale using manual processes and tools.
  • Architect, Design and Maintain Data Quality Dashboards
  • Create a set of data quality certification standards and implement a process to certify various data sets and maintain/improve certification levels
  • Help describe data quality issues in business terms
  • Coordinate with data custodians and process owners to fix data quality issues
  • Report to Enterprise Data Governance Board or authorized representatives the status and progress related to data quality and mitigation of issues
  • Ensure common understanding and maintenance of Business Rules surrounding firm's data.
  • Provide guidance on projects and initiatives to interpret and develop business rules and alignment and assurance of data quality targets
  • Evangelize, promote and market to improve utilization of Data Quality Services developed as part of the function.
  • Provide input into developing overall management and governance standards and policies to ensure the accuracy, protection and quality of data and to promote a data quality discipline throughout the Firm

Travel Requirements May require travelling a few times an year to conferences and organizational meetings


Technical Skills, Qualifications and Experience

  • Strong experience in data architecture, data modelling, data warehousing and database design. Some experience in a leadership role
  • Degree in computer science (Degree in Statistics, Mathematics would be highly regarded)
  • Significant knowledge and experience in data warehousing, data-mining, ETL tools
  • Experience in developing complete data models in a manner that is understandable to a non-technical audience
  • Broad and deep understanding of the Firm, how we operate, how we interact with our clients and our internal business processes

Communication and management skills

  • Outstanding communication and presentation skills able to engage with stakeholders at all levels
  • Experience in supervising and mentoring a team of architects and engineers
  • Capable of working independently and in a geographically and culturally diverse team
  • A critical, analytical, exception finding, hacker mindset
  • Process oriented, structured, operation building focus