Advisory Analytics Consultant Manager

Job Requirements:

1. Strong educational background in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related field. An advanced degree is a plus.
2. 5 –10 years of experience in analytics consulting or a similar role, with a track record of leading projects and managing teams.
3. Proficiency in analytics tools and programming languages such as Python, R, SQL, Tableau, or Power BI.
4. Exceptional communication, problem-solving, and stakeholder management skills.
5. Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies is a bonus.

Keys Responsibilities:

1. Collaborate with clients to understand their business objectives, challenges, and analytics needs.
2. Serve as a trusted advisor, providing recommendations on leveraging analytics to drive decision-making and improve performance.
3. Present insights, findings, and actionable strategies to senior stakeholders and executive-level clients.
4. Lead and manage multiple analytics projects simultaneously, ensuring timely delivery and alignment with client expectations.
5. Define project scope, timelines, and deliverables while monitoring performance against objectives.
6. Mitigate risks and resolve project-related issues proactively.
7. Design and implement advanced analytics solutions using statistical models, machine learning, and data visualization techniques.
8. Ensure the accuracy, quality, and relevance of all analytical outputs.
9. Mentor and lead a team of analysts and consultants, fostering professional growth and knowledge sharing.
10. Evaluate team performance and provide constructive feedback.
11. Identify opportunities to expand the analytics practice by introducing new techniques or technologies.
12. Contribute to business development efforts, including proposal writing and presenting analytics capabilities to prospective clients.
13. Work closely with other advisory teams, such as strategy, operations, and technology, to deliver integrated solutions.
14. Collaborate with data engineering teams to ensure data pipelines and architectures support analytics needs.
15. Act as a liaison between technical teams and business stakeholders to ensure alignment.
16. Develop and deliver comprehensive reports, dashboards, and visualizations to convey analytics insights effectively.
17. Maintain thorough documentation of analytics processes, methodologies, and project outcomes.