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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 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. 


Travel:
  • As per business requirements


$180,300 - $308,000 a year
The following information is required by pay transparency legislation in the following states: CA, CO, HI, NY and WA. This information applies only to individuals working in these states. 

The anticipated starting pay range for Colorado is: $180,300 - $264,440.

The anticipated starting pay range for Hawaii and New York (not including NYC) is: $191,900 - $281,490.

The anticipated starting pay range for California, New York City and Washington is: $210,000 - $308,000.

Based on eligibility, compensation for the role may include variable compensation in the form of bonus, commissions, or other discretionary payments.

These discretionary payments are based on company and/or individual performance, and may change at any time.

Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. 

Information on benefits offered is here.


#LI-VM1

#LI-Remote

#LI-USA

#rackspace

Average salary estimate

$244150 / YEARLY (est.)
min
max
$180300K
$308000K

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What You Should Know About Practice Manager, Data Science, AI and ML, Rackspace

Join Rackspace as a Practice Manager of Data Science, AI, and ML, where your expertise will shine! In this dynamic role, you'll lead a talented team of professionals dedicated to delivering innovative AI and ML solutions. As a seasoned manager, you will engage directly with customers, ensuring that their project requirements are met while fostering a collaborative environment with both business and technical teams. You'll be the bridge connecting technology with tangible business value, educating clients on the transformative power of data science and guiding them towards adopting cloud solutions. This position is perfect for those who not only thrive in a technical capacity but also enjoy nurturing talent by mentoring Data Science Architects, Data Scientists, and ML engineers on your team. With responsibilities that include strategic planning, operational tasks, and regular feedback sessions with your team members, you'll play an integral part in building and maintaining Rackspace’s leadership in the data science sector. A critical aspect of your role is to create impactful relationships with clients, ensuring that they advocate for cloud solutions. Plus, you’ll have the opportunity to attend industry events and travel up to 50% of the time, enhancing Rackspace’s presence in the data science community. This is your chance to be at the forefront of AI and ML innovations—come lead the way!

Frequently Asked Questions (FAQs) for Practice Manager, Data Science, AI and ML Role at Rackspace
What are the primary responsibilities of a Practice Manager in Data Science, AI, and ML at Rackspace?

As a Practice Manager at Rackspace, you will oversee the development and delivery of data science and AI projects, act as the primary technical liaison between customers and engineering teams, and manage a team of Data Science professionals. Your role will also involve strategic planning to ensure operational efficiency and quality, supporting sales teams, mentoring your team members, and driving best practices in AI and ML solutions.

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What qualifications are required for the Practice Manager position at Rackspace?

Candidates for the Practice Manager in Data Science, AI, and ML at Rackspace should have over 12 years of experience in customer-facing technology roles, at least 7 years in architecting data science and AI solutions, and 6 years working specifically with AWS or other public cloud services. Advanced degrees like a Master's or Ph.D. in Computers or Data Science, along with AWS or other cloud certifications, are highly preferred.

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How does Rackspace support the professional development of a Practice Manager in Data Science, AI, and ML?

Rackspace encourages continuous learning and professional growth for Practice Managers by providing mentorship opportunities, regular 1:1 meetings to share feedback, and avenues for team members to pursue their career development goals. You'll also be involved in creating feedback channels that contribute to the quality of delivery and risk management.

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What kind of team will I lead as a Practice Manager at Rackspace?

As a Practice Manager at Rackspace, you will lead a diverse and skilled team that includes Data Science Architects, ML Engineers, and Data Scientists. You will mentor and guide them in their professional development while fostering an aspirational work culture and ensuring that deliverables meet client expectations.

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What travel expectations come with the Practice Manager role at Rackspace?

The Practice Manager role at Rackspace has travel requirements of up to 50%. This travel is essential for meeting with clients, attending industry events, and strengthening partnerships to ensure the successful delivery of AI and ML solutions.

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Common Interview Questions for Practice Manager, Data Science, AI and ML
Can you describe your experience with AI and ML solutions in a customer-facing role?

In your response, highlight specific projects you've led that involved designing and implementing AI and ML solutions. Emphasize your interaction with clients, how you gathered requirements, and the technologies you employed to achieve successful outcomes.

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How do you prioritize tasks and manage your team's workload?

Share your approach to prioritizing tasks by explaining how you assess project deadlines, team skills, and potential roadblocks. Discuss tools or methodologies, like agile frameworks, that help you balance workload effectively.

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What strategies do you use to build relationships with clients?

Discuss your techniques for effective communication, regular check-ins, and the importance of understanding client goals. Highlight any experiences where relationship-building led to improved project outcomes.

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Describe a challenging project you managed. What did you do to ensure its success?

Provide an example of a project that faced significant hurdles. Discuss your problem-solving skills, how you rallied the team, and the specific steps you took to keep the project on track.

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How do you mentor your team members?

Talk about your mentoring style, how you set development objectives, and the frequency of feedback sessions. Mention tools or methods you use to track their growth and the positive impact of mentorship on team dynamics.

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Can you give an example of how you implemented an agile methodology in your previous roles?

Explain a specific scenario where you successfully adapted an agile approach to project management. Describe the challenges faced before implementing it and how the change improved workflow and outcomes.

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What is your understanding of AWS services related to Data Science and ML?

Articulate your familiarity with AWS services such as SageMaker, Redshift, or Kinesis. Provide details on how you've integrated these services into your past projects to drive data science outcomes.

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How do you stay updated with the latest trends in AI and ML?

Share your methods for keeping up with industry trends, whether it be through online courses, attending conferences, reading relevant journals, or participating in professional networks.

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What is your approach to ensuring quality in project delivery?

Discuss how you set quality standards, conduct reviews, and incorporate client feedback. Highlight experiences where you ensured effective communication among stakeholders to maintain high-quality standards.

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How do you align your team's efforts with the overall business goals of the company?

Describe how you ensure that your team's objectives are aligned with the larger business goals at Rackspace by setting measurable targets and communicating the vision effectively to your team.

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Founded in 1998, Rackspace provides multi-cloud computing solutions and services. Offering advising to customers based on business challenges, designing solutions, building, and managing solutions. The company is headquartered in San Antonio, Texa...

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Full-time, remote
DATE POSTED
December 12, 2024

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