Data Analytics Consultant Job Description

How do you write a job description for a Data Analytics Consultant?

Are you looking to make an impact by helping agencies meet their mission goals through successful implementation and operation of their regulatory, mission or compliance programs? Are you ready to help our clients mitigate risks that arise from transformational core business operational change or ongoing operations? Are you interested in helping clients transform how they operate their business to be more effective? If so, Deloitte's Regulatory Compliance team could be the place for you! Our team brings professionals with diverse skill-sets including deep experience in industry, AI-enabled data analytics, statistical modeling, and cloud technologies to help our clients preserve their reputation and public trust of their agencies while managing regulatory demands.

This sample Job description explainer offers guidance on key sections that are important to include for clarity, as well as suggestions for promoting the position. It provides a list of duties, responsibilities, tasks, requirements, demands for setting job expectations and the employee's ability to perform the work as described. However, it’s often not construed as an exhaustive list of all functions, responsibilities, skills and abilities.

What does a Data Analytics Consultant do?

Responsibilities:

• Perform day-to-day quantitative risk analysis including the development, maintenance, and operations of a suite of advanced analytical, econometric, and AI models and business intelligence tools.
• Be accountable for interpreting and translating results, trends, and takeaways to team members, clients, and executive leadership with varying levels of subject matter knowledge.
• Drive the production of predictive analytic reports, responsible for executing key modeling governance activities around change management, performance monitoring, and testing, in alignment with industry best practices.
• Develop and lead new, innovative analyses which may include data set manipulation and transformation, piloting of cutting-edge AI and machine learning analytical techniques and technologies, and transformation of static reporting into dynamic visualizations.
• This is a cross-functional role where teams will interact with data collection, reporting, system designers, architects, database administrators, and cyber risk professionals to assist, from a business prospective, in overall production processes to enhance the value delivered to our clients.

Qualifications:

• 3 + years of experience with data quality analysis, statistical analysis and/or modeling, financial or cost analysis, internal controls, and/or external/internal financial audit.
• SAS experience required.
• Experience across the entire model development lifecycle, including interacting with model risk management teams and executing model governance best practice.
• Deep technical understanding, including proficiency in an analytical programming language, such as SAS, Python, or R, to provide clear technical direction, mentoring and growing the skills of your team (minimum 2 years of experience).
• Hands-on development experience of AI and machine learning models, packages, or COTS tools, with corresponding model risk management and governance of AI and machine learning (e.g., bias).
• Strong executive presentation skills, able to strategically and effectively communicate with both external and internal stakeholders, as well as collaboratively across business units, technology, and policy teams.
• Bachelor's Degree in Economics, Finance, Statistics, Mathematics, Computer Science, Management Information Systems, Engineering, Business Analytics disciplines, or related area.
• Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.
• Ability to obtain and maintain the required clearance for this role.

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