Practice Manager, Data Science, AI and ML
Job Summary
Job Description
The Practice Manager for Data Science, AI, and ML at Rackspace is a technical leadership role requiring 12+ years of experience. Responsibilities include leading a team of data scientists, ML engineers, and architects, delivering successful professional services engagements, and acting as a technical liaison between clients and engineering. This role involves driving project success, shaping sales opportunities, developing practice growth strategies, building AWS alliances, and mentoring direct reports. The manager will actively participate in delivering AI/ML solutions, educating customers, and fostering a strong team culture. The position demands strong communication, leadership, and technical skills, including expertise in AWS data analytics and AI/ML services, agile methodologies, and software development.
Must have:
- 12+ years customer-facing experience
- 7+ years building Data Science/AI solutions
- 6+ years AWS or other public cloud experience
- Deep AWS Data Analytics & AI/ML Services knowledge
- Agile methodology understanding
- Master's or Ph.D. in Computer Science/Data Science
Good to have:
- AWS, Azure, or GCP Certified ML Specialist
7 skills required
Job Details
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 who understands how to run successful professional services engagements, 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 andstrategies, 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 steam 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 :
- As a Practice Manager, you will be technically focused but also will understand business planning implementation
- Be the lead technical liaison between customers and engineering resources.
- Provide tactical scope and work directly with the business representatives/customers to understand the requirements driving the need for a solution to be developed
- Lead teams of both business and technical colleagues throughout the course of the project, and communicate with each of them effectively
- Ensure that all the appropriate questions are asked and verify that nothing crucial to the success of the project is overlooked
- Be an AI and ML evangelist by educating a variety of customers on the value of data science and AI Solutions.
- Help customers transition to the cloud in a high-value migration approach that leverages best-of-breed designs and practices delivered in an agile model.
- You will play an active role in delivering modern AI and ML solutions for clients, including generative AI, cognitive computing, and cloud services
- Establish credibility and build impactful relationships with our customers to enable them to be cloud and Data science and AIadvocates
- Lead and participate in deep solutions and architectural discussions to build confidence and ensure customer success when building platforms and services on the AWS platform.
- Conduct deep-dive “hands-on” education/training sessions to transfer knowledge to customers interested in AWS and to ensure our Rackers are up to date
- Attend and present valuable information at Industry Events
- Collaborate in setting up Go to Market strategies for Data science and AI.
- Traveling up to 50% of the time
- Hold regular 1:1 meetings with direct members of your team to share feedback, provide an avenue for trusted communications, and help with their career development.
- Foster an aspirational working culture within team
- Own practice Growth & Productivity
- Provide coaching for team members and help establish and track goals
- Act as a communication conduit to provide information to the practice membership
- Create sources of feedback for practice members to promote consistent quality of delivery and support the professional development of practice members
- Work with presales architects on designing and validating proposals and SOWs to ensure high-quality and deliverable engagements to drive successful outcomes for customers
- Support tasks related to hiring including interviewing, supporting provisioning and evaluation of technical assignments, and onboarding new Rackers
- Understand metrics of how the practice is performing and support initiatives to improve our operations and effectiveness
- Identify and drive internal initiatives for the practice related to offer development, improving operations, improving our standard operating process, development of reusable delivery artifacts, and promoting knowledge within the organization
Requirements
- 12+ years of experience in customer-facing software/technology, data analysis, or consulting.
- Minimum7+ years of experience architecting and building Data science and AI solutions.
- Minimum6+ years of experience with AWS or other public cloud Data Science solutions
- In-depth understanding and professional experience with AWS Data Analytics and AI/ML Services
- Demonstrated knowledge of software development tools and methodologies
- Solid understanding of agile methodologies
- Master or Ph.D. in Computers and/or Data Science.
- AWS, Azure or GCP Certified ML Certified Specialist.
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