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Senior Manager, Data Science Management

Company Description

It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.

Job Description

You will manage a team of 4-6 Data Scientists as they create Machine Learning models that drive our growth across all products. You will interact with stakeholders in departments across the company and identify opportunities for Data Science to enhance our business, match the optimal machine learning techniques to the specific business need, and then build the models that get the job done. 

This is an opportunity for the right candidate to go from end-to-end in the process, from recognizing a problem to implementing the solution, and integrating it with the business teams.

What you get to do in this role:

  • Solicit requirements for Data Science models, including what data they will use and how the company will use them after they are built
  • Define the variables and their structure, and extract the data from our data warehouse and/or guide specialists to do so
  • Build predictive models that are accurate, robust, and informative in ways that help our business grow even faster
  • Teach our business teams what the models do, what the results mean, and how they improve decision-making

Qualifications

To be successful in this role you have:

  • Master’s Degree, PhD preferred with 6 + years experience with AI/ML
  • 3+ years of experience managing AI/ML engineering teams with proficiency in providing feedback to work group strategies, policies, and plans
  • Ability to manage several projects simultaneously, scopes projects, realistically estimates work and drive stakeholder/end-user alignment
  • Successful project experience in Data Science in an Enterprise setting, and extensive use of methods like: regression, decision trees, random forests, GBMs, Bayesian methods, neural networks/deep learning, support vector machines, recommendation engines, k-nearest neighbor, NLP, Business Process Mining or HMM
  • 4+ years of experience in building predictive models, defining variables, variable selection, and measuring model quality
  • Experience in model explainability, delivering model explanation/reason codes along with predictions/recommendations
  • Expertise with scripting in R, SAS, Python, or similar tools
  • Demonstrated ability to drive creativity and innovation in AI projects. 
  • Deep knowledge and hands-on experience in LLMs, deep learning, NLP, NLU, BERT, GPT, NLP, and related AI technologies.
  • Experience in manipulating large datasets and using databases, performing SQL queries
  • Experience with Azure ML, Azure Data Lake, and/or Databricks
  • Special consideration for applicants experienced in:
    • Driver/impact analysis
    • Model validation
    • Software product usage data
  • Excellent presentation and communication skills 

GCS-23

Not sure if you meet every qualification? We still encourage you to apply! We value inclusivity, welcoming candidates from diverse backgrounds, including non-traditional paths. Unique experiences enrich our team, and the willingness to dream big makes you an exceptional candidate!

For positions in this location, we offer a base pay of $192,700 - $337,300, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.

Additional Information

Work Personas

We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work. Learn more here.

Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. 

Accommodations

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact [email protected] for assistance. 

Export Control Regulations

For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. 

From Fortune. ©2024 Fortune Media IP Limited. All rights reserved. Used under license. 

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Average salary estimate

$265000 / YEARLY (est.)
min
max
$192700K
$337300K

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What You Should Know About Senior Manager, Data Science Management, ServiceNow

Are you ready to take the lead in driving impactful data strategies? Join ServiceNow as a Senior Manager, Data Science Management in beautiful Kirkland, Washington. Here you will manage a talented team of 4-6 Data Scientists as they create groundbreaking Machine Learning models that will turbocharge our growth across all products. In your role, you'll collaborate with stakeholders from various departments, spotting opportunities to leverage Data Science to enhance our business performance. You’ll dig into defining the right machine learning techniques to tackle specific business challenges while also building robust models that result in actionable insights. From defining requirements to guiding data extraction and instructing our business teams on how to use the predictive models effectively, your contributions will be essential. With a focus on creativity and innovation, you’ll turn complex datasets into business intelligence that drives informed decision-making. At ServiceNow, you won’t just be managing data; you’ll be shaping the future of how organizations operate using our powerful AI-enhanced technology. If you possess a passion for Data Science, along with a strong background in AI/ML engineering and team leadership, we want to hear from you!

Frequently Asked Questions (FAQs) for Senior Manager, Data Science Management Role at ServiceNow
What are the key responsibilities of a Senior Manager, Data Science Management at ServiceNow?

As a Senior Manager, Data Science Management at ServiceNow, you will lead a team of data scientists in developing and implementing machine learning models. Your key responsibilities will include soliciting requirements for projects, defining the structure of data variables, and building predictive models aimed at enhancing business growth. You’ll also be responsible for teaching business teams about the functionality of these models, ensuring they understand how to leverage insights to make better data-driven decisions.

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What qualifications are necessary for the Senior Manager, Data Science Management position at ServiceNow?

To excel in the Senior Manager, Data Science Management role at ServiceNow, you need a Master’s Degree or preferably a PhD, combined with at least 6 years of experience in AI/ML. Additionally, at least 3 years of management experience leading AI/ML engineering teams is required. Proficiency with multiple data science methods and tools is crucial, alongside experience in building predictive models and effective project management capabilities.

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How can the Senior Manager, Data Science Management influence business growth at ServiceNow?

The Senior Manager, Data Science Management at ServiceNow plays a pivotal role in identifying data science opportunities that drive business growth. By constructing effective machine learning models that provide actionable insights, this position directly influences decision-making across various departments. This collaboration enhances operational efficiency and fosters innovation, allowing the company to stay ahead in a competitive market.

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What tools and technologies will be used by the Senior Manager, Data Science Management at ServiceNow?

In the Senior Manager, Data Science Management role at ServiceNow, you will work with a variety of advanced tools and technologies including R, Python, Azure ML, Azure Data Lake, and Databricks. Familiarity with SQL for database manipulation and the ability to handle large datasets is also essential. Knowledge in LLMs, NLP, and other AI technologies will enable you to effectively manage projects and drive innovative solutions.

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What is the work culture like for the Senior Manager, Data Science Management at ServiceNow?

The work culture at ServiceNow for the Senior Manager, Data Science Management is flexible and collaborative. The company promotes inclusivity and encourages its employees to pursue creative solutions to challenges. You will be part of a supportive environment where diverse perspectives are valued, and opportunities for professional development are abundant. With an emphasis on making the world work better for everyone, ServiceNow provides a positive atmosphere that fosters innovation and teamwork.

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Common Interview Questions for Senior Manager, Data Science Management
Can you describe your experience managing AI/ML engineering teams?

When answering this question, focus on specific instances of how you've led teams, highlighting your approach to project management and team dynamics. Illustrate your experience with setting goals, providing constructive feedback, and driving results in AI/ML projects.

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What methodologies do you prefer when developing predictive models?

Discuss the methodologies you are most comfortable with, such as decision trees, regression analysis, or neural networks. Be prepared to explain why you favor certain methods over others and how they align with the specific business needs you've encountered.

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How do you ensure model explainability in your data science projects?

When answering, emphasize your techniques for ensuring clarity in how models operate, such as using visual aids or providing straightforward explanations of results to business teams. Discuss the importance of model interpretation in driving adoption of data science solutions.

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Can you give an example of a challenging project you've managed in data science?

Share a specific example that showcases your problem-solving skills and ability to navigate complexities. Discuss your role, the challenges you faced, and how your leadership contributed to a successful outcome.

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What strategies do you use to manage multiple data science projects simultaneously?

Your response should detail how you prioritize tasks, delegate responsibilities, and maintain communication with stakeholders. Highlight any project management tools or methods you employ to keep projects on track and within scope.

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What has been your approach to collaborating with stakeholders from different departments?

Highlight your communication skills and experience in building rapport with non-technical stakeholders. Describe how you identify their needs and ensure the data science solutions you provide align with their goals.

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How do you handle setbacks in data science projects?

Provide examples of how you've managed setbacks proactively by reassessing strategies, refining models, or gathering additional data. Stress the importance of adaptability and learning from outcomes to enhance future projects.

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What role do you believe AI/ML will play in the future of business?

Discuss your vision for AI/ML's role by referencing trends, advancements, and potential industry impacts. Emphasize your enthusiasm for innovative applications of AI and how they could transform business operations.

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How do you stay updated on advancements in data science and AI technologies?

Mention how you engage with the data science community through professional networks, conferences, webinars, or online courses. Highlight any research or continued education that keeps you informed about the latest developments.

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Can you explain a complex AI concept in simple terms?

Prepare to demonstrate your ability to communicate technical information clearly. Pick a complex topic you are familiar with and explain it without jargon, ensuring that it remains accessible to all audiences.

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CULTURE VALUES
Inclusive & Diverse
Mission Driven
Rise from Within
Diversity of Opinions
Work/Life Harmony
Empathetic
Feedback Forward
Take Risks
Collaboration over Competition
BENEFITS & PERKS
Medical Insurance
Dental Insurance
Vision Insurance
Mental Health Resources
Life insurance
Disability Insurance
Health Savings Account (HSA)
Flexible Spending Account (FSA)
Conferences Stipend
Paid Time-Off
Maternity Leave
Equity
FUNDING
DEPARTMENTS
SENIORITY LEVEL REQUIREMENT
TEAM SIZE
EMPLOYMENT TYPE
Full-time, on-site
DATE POSTED
December 11, 2024

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