Job Abstract

Goldman Sachs Asset Management Business Intelligence Vice President will contribute to leading programs by delivering business and artificial intelligence analytics initiatives. This role will combine accountability and responsibility for delivering automated solutions and business analytics, by taking advantage of artificial intelligence, process automation and data visualization tools, to generate business value.

As a business intelligence specialist, your efforts will involve providing solutions to impactful business initiatives. You will be engaging directly with business representatives and subject matter experts to drive value in line with Goldman Sachs Asset Management strategy while ensuring algorithms, low code assets, and user experience are continually improved to meet organization growth strategy.

Fulfilling Your Potential

• Analyze big data and undertake exploratory data analysis while observing best practices for experimentation / analysis
• Perform data preparation, data blending, data visualization
• Develop business intelligence applications and present outcomes
• Design indicators of business intelligence application performance and risk metrics
• Synthesize analysis results to inform business outcomes
• Identify, escalate and resolve systems and algorithm performance trends or issues
• Deliver business intelligence products in the context of your organizations change agenda
• Track and report progress on projects, adhering to the solution delivery lifecycle
• Seek information / guidance / opportunities from inside and outside of your firm / industry to corroborate outcomes
• Collaborate with other solution experts / advisors to share ideas / code through showcasing outputs
• Extend / modify analysis / development based on observations of data, process limitations and implications of outcomes
• Manage team / teams of core and embedded specialists Business Intelligence Specialists
• Lead oversight of client / customer / stakeholder engagements to drive low code opportunities
• Partner with Engineering to ensure low code is provisioned in the context of your firms’ wider technology architecture strategy
• Shape, define and execute on the Business Intelligence specialist career path
• Advise and become advisor for evolving solution applications while keeping a view of full low code toolkit through solution design forums
• Contribute to ever changing Business Intelligence risk and governance framework
• Partner with internal and external firm innovation partners to drive adoption of new technologies, contributing to ongoing incubation of new low code applications
  

Basic Qualifications

• 7+ years’ experience in (1) Business Intelligence and (2) Project, Communication and Stakeholder Management
• Bachelor’s degree or equivalent in Science, Technology, Engineering or Mathematics
• Relevant experience in Consumer, Financial, Social Media, FinTech
• Practitioner in business intelligence and/or artificial intelligence methodologies and their value / limitations
• Software design and application of software according to the day-to-day realities of the business
• Knowledge of data related emerging trends and issues including financial regulation
  

Soft Skills

• Fast learner and effective communicator of new / complex information
• Self-motivated team player who is able to define, structure and prioritize work, but who has the flexibility to change priorities when circumstances dictate
• Able to develop cooperative and constructive working relations with strong cultural awareness
• Confidence to challenge and be innovative

Preferred Qualifications

Business

• Financial Engineering and / or Investment Management experience
• Able to contextualize analysis in Confluence, JIRA, Microsoft Applications, etc.
  

Solution Delivery

• Experience with implementing according to solution delivery frameworks such as Agile, Six Sigma, Waterfall, etc.
• Experience in the practice of continuous integration / continuous deployment

Business Intelligence

• Working knowledge of analytics applications (i.e. Alteryx, Tableau, Qlik)
• Working knowledge of workflow applications (e.g. Appian, unqork, Xceptor)
• Working knowledge of database tools (e.g. Elasticsearch, MS SQL Server)

Artificial Intelligence

• Working knowledge of artificial intelligence programming languages (e.g. Python, R)
• Working knowledge of artificial intelligence scientific computing packages (e.g. Scikit-Learn, Pandas, NLTK)
• Working knowledge of artificial intelligence platforms including robotics (e.g. Automation Anywhere, Anaconda, GitHub/Lab, Jupyter Hub, UiPath)