Research Management System Manager

Full Time
  • Full Time
  • Toronto

Black Creek Investment Management Inc.

Black Creek Investment Management Inc. (“Black Creek”), an employee-owned Toronto-based investment advisory firm specializing in the management of global equities for clients in North America, Europe, and Australia. We are seeking an experienced Research Management System Manager to join a dynamic and growing team. Additional information about Black Creek is available at The company has recently selected Bloomberg Anywhere as the key tool to manage all of our unique investment research that underpins our investment decisions. This role is responsible for the successful adoption of and value creation from this system. Reporting to the Head of Information Management and Technology, the successful applicant will be responsible for the configuration, management, enhancement, and daily operation of Black Creek’s Research Management System (RMS). This role is of significant strategic importance to the organisation as it is the core system from which portfolio managers (PM’s) and analysts generate their investment ideas and insights. Role Outcomes The role is focused on achieving specific outcomes:·       Understanding the information needs of our investment team·       Surfacing and sharing unique insights from our research repository·       Achieving enthusiastic adoption of the RMS by the investment teamSpecific duties may include the following, depending on the skill set of the successful candidate:Responsibilities·       Assume the role of application owner of the RMS·       Provide direct support and training to PM’s on the use of the RMS·       Enhance the system with new data, tools, analytics and reports·       Manage the vendor relationship Qualifications·       Experience: Minimum 3 years of experience in investment research, library science, data science, or data management roles·       Industry experience: Financial services or asset management industry experience is an asset·       Skills: Demonstrated expertise in at least one of the following areas: o  Investment research management, creation, or analysis o  Analysis of unstructured data o  Data organization and management theory·       Bloomberg Terminal: Familiarity with the software and has working knowledge of the RMN and DS NOTE functionality·       Technical: Familiarity with one or more of following is an asset: o  BQuant / BQL o  Python or R o  Using API’s·       Education:  Minimum Bachelor’s degree or equivalent training in Finance, Information Systems, Library Science, Data Science, or a related discipline·       Language:  Business English, with strong listening and comprehension skills·       Communication: training and teaching skills desired, for audiences of all skill levels·       High degree of integrity, work ethic, commitment and professionalism·       Proven prudence, thoroughness, and strong attention to detail·       Excellent analytical and organizational skills·       Exceptional interpersonal, social, and relationship building skillsThis role is dynamic and is expected to evolve substantially over time with expanding areas of responsibilities in a team environment. Only selected candidates will be contacted.Given that this role requires significant interaction with other employees, the successful candidate will work most days at Black Creek’s office.

Black Creek does have a hybrid work policy, which can allow for some flexibility in work location at times. Please forward resume to the attention of David Yackness via Black Creek Investment Management Inc. is an equal opportunity employer and prohibits discrimination against any employee or prospective employee because of gender, race, ancestry, religion, disability, sexual orientation, marital status or any other characteristics protected under the Ontario Human Rights Code and the Canadian Charter of Rights and Freedoms. Black Creek welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process. 


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