Full-Time Practice Manager, Data Science, AI and ML

Overview Practice Managers are expected to be subject matter experts capable of leading a group of like-minded Rackers in the Data science, AI and ML practice. This role includes both deliveries in a Professional Services Data Science Architect or an SME role on customer engagements as well a commitment to ensuring the overall success of the practice as a leader.

As an experienced Data Science Practice Manager you will help drive projects that deliver successful outcomes for customers wanting to do Data science and AI/Ml projects. Successful candidates will have demonstrated the ability to think strategically about businesses, create technical definitions around customer objectives in complex situations, develop solutions and strategies, motivate & mobilize resources, provide technical guidance, and deliver results.

The ability to connect technology with measurable business value is a critical component to be successful in this role. We seek team members who are self-motivated, driven, collaborative, and passionate about deep cloud adoption and technology in general.

As a manager you will have a stream of direct reports that include Data Science Architects, Data Scientists, ML engineers who you will mentor and assist with their development.

In addition to managing your direct reports, you will act as a leader within the practice, supporting objectives such as overall quality and efficiency of our delivery, supporting sales teams with shaping and reviewing opportunities, creating growth strategies for practice, and building and maintaining AWS alliance and partner relationships.

Support operational tasks such as resourcing support or hiring and onboarding new Rackers. Strong communication skills, the ability to lead and inspire others, and emotional intelligence are critical to your success in this role.

What you'll be doing:

• Be technically focused but also understand business planning implementation
• Be the lead technical liaison between customers and engineering resources
• Provide tactical scope and work directly with business representatives/customers to understand the requirements
• Lead teams of both business and technical colleagues throughout the project
• Ensure all appropriate questions are asked and nothing crucial is overlooked
• Be an AI and ML evangelist
• Help customers transition to the cloud
• Play an active role in delivering modern AI and ML solutions
• Establish credibility and build relationships with customers
• Lead and participate in solutions and architectural discussions
• Conduct deep-dive education/training sessions
• Attend and present at industry events
• Collaborate in setting up Go to Market strategies
• Travel up to 50% of the time
• Hold regular 1:1 meetings with team members
• Foster an aspirational working culture
• Provide coaching for team members and help establish goals
• Act as a communication conduit
• Create sources of feedback for practice members
• Work with presales architects on designing and validating proposals
• Support tasks related to hiring (interviewing, provisioning, evaluation)
• Understand metrics of practice performance and support initiatives
• Identify and drive internal initiatives related to offer development

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