Senior Principal Data Scientist, AaaS

2 Months ago • 15 Years + • Data Analysis

Job Summary

Job Description

Dun & Bradstreet is seeking a Senior Principal Data Scientist, AaaS to join their Data & Analytics group. This role involves engaging with prospects to identify analytical solutions for customer problems, working with clients and Data Scientists to define project scope, deliverables, timelines, and pricing. The position leads the design, development, and deployment of Analytics as a Service (AaaS) solutions, integrating advanced analytics, AI, machine learning, and platform strategy. Responsibilities include managing all customer aspects of modeling engagements, researching business issues, recommending solutions, and driving innovation in Global Analytic Solutions using statistical models and client requirements. The role also involves creating new data and analytics-driven opportunities, developing solution proposals, collaborating with sales teams, and acting as a Subject Matter Expert in predictive modeling and advanced big data analytics.
Must have:
  • Master's Degree or Ph.D. in a quantitative field
  • 15+ years of experience in analytics and business
  • Proven track record in machine learning, AI, statistical analysis, and predictive modeling
  • Experience delivering analytics at scale via AaaS
  • Background in consulting, enterprise platform design, or SaaS analytics
  • Strategic and execution mindset
  • Commercially focused mindset with client relationship building skills
  • Experience writing proposals and responding to RFPs
  • Deep interest in Gen AI trends and use cases
  • Proficiency in Microsoft Office Suite
  • Ownership mindset, problem-solving, curiosity, and proactive action
  • Continuous growth mindset and learning
  • Fluency in English and relevant market languages
Good to have:
  • Build relationships with external data vendors
  • Create sales collateral, solution documentation, and RFP responses
  • Identify opportunities for testimonials, white papers, and case studies
  • Lead architecture and delivery of AaaS solutions
  • Design and oversee deployment of advanced analytics and ML models into production

Job Details

Why We Work at Dun & Bradstreet
Dun & Bradstreet combines global data and local expertise to help clients make smarter decisions. With 6,000+ people in 31 countries, we are a team of diverse thinkers and problem solvers who all share a common curiosity: to find new ways to turn data into value. If you share this curiosity and want to be part of a future-ready company, come join us! Learn more at dnb.com/careers.

As part of a new team within Dun & Bradstreet's Data & Analytics group, you will engage with prospects to determine where analytical solutions and consultancy will aid in solving customer problems. You will work with the customer and Data Scientists to agree design, deliverables, timelines and pricing that secures customer engagement. This role leads the design, development, and deployment of Analytics as a Service (AaaS) solutions. It blends advanced analytics, AI, machine learning, and platform strategy to deliver robust and automated data science capabilities across business units and to external clients. You will be responsible for all customer aspects of the modeling engagement, including design, development, validation, calibration, documentation, approval, implementation, monitoring, and reporting. You will research complex business issues, bring strong business acumen and recommend solutions, including model features, end products and any data required to support growing Dun & Bradstreet initiatives.

Responsibilities:

  • Based upon customer needs, drive the development and innovation of Global Analytic Solutions inclusive but not limited to statistical models based on D&B’s established best practices, methodologies, and tools.
  • Create new data and analytics-driven opportunities with clients
  • Work on prescriptive ROI models for the customer and gather client requirements by fully understanding their business needs
  • Develop solution proposals, outlining how our products, data and analytical capabilities can address specific challenges and add economic value to the client’s business
  • Collaborate with sales and client success when necessary to participate in strategic client meetings; this could be regular check ins, periodic business reviews, industry reviews, etc.
  • Create sales collateral, solution documentation, and RFP responses; identify opportunities for testimonials, white papers, and/or case studies
  • Establish and maintain strong relationships with key internal and external stakeholders.
  • Serve as a Subject Matter Expert on predictive models within the Advanced Analytic Services team and with business users; consult with the business, as appropriate, on predictive modeling solutions.
  • Explore advanced big data analytics in emerging areas such as machine learning and artificial intelligence. Identify business relevance of new methods and work with cross functional teams to create prototypes, assist in creating business case, and go to market strategy.
  • Lead the architecture and delivery of AaaS solutions that automate end-to-end analytics workflows.
  • Design and oversee the deployment of advanced analytics and ML models into production environments (e.g., via MLOps pipelines).
  • Provide delivery guidance for various technology areas within data management, business intelligence and analytics.
  • Build relationships with external data vendors and aggregators to support analytical initiatives and products, building and testing Proof of Concept algorithms that meet business needs.
  • Act as a trusted solutions advisor to the sales team and their clients, helping to understand the clients core needs/pain points, business, and technical requirements
  • Search for new alternative data based on the use cases - customer problems by business units, data quality and additional product needs.

Essential Skills and/or Certifications:

  • Master’s Degree or Ph.D. in a quantitative/applied field preferred (Finance, Statistics, Econometrics, Computer Science, Operations Research, Mathematics, Engineering).  
  • 15+ years of experience in analytics and business.
  • Proven track record of using machine learning and AI, advanced software, statistical analysis, predictive modeling.
  • Proven success in delivering analytics at scale via AaaS or similar reusable analytics frameworks.
  • Background in consulting, enterprise platform design, or SaaS analytics.
  • Be strategic but with an execution mindset. Be able to lead the innovation ideas as well as deliver on the execution, with evidence of developing new ideas or launching new initiatives.
  • Have a commercially focused mindset, with experience from customer focused projects. Able to manage and build relations with key stakeholders to understand problems and formulate solutions.
  • Hands on experience from writing proposals, respond to RFPs, design POCs etc.
  • Deep interest and knowledge in the evolving space of Gen AI; industry trends, applicable use cases etc.
  • Proficiency in Microsoft Office Suite skills.
  • Show an ownership mindset in everything you do. Be a problem solver, be curious and be inspired to take action. Be proactive, seek ways to collaborate and connect with people and teams in support of driving success.
  • Continuous growth mindset, keep learning through social experiences and relationships with stakeholders, experts, colleagues and mentors as well as widen and broaden your competencies through structural courses and programs.
  • Where applicable, fluency in English and languages relevant to the working market.

All Dun & Bradstreet job postings can be found at https://www.dnb.com/about-us/careers-and-people/joblistings.html and https://jobs.lever.co/dnb. Official communication from Dun & Bradstreet will come from an email address ending in @dnb.com.

Notice to Applicants: Please be advised that this job posting page is hosted and powered by Lever. Your use of this page is subject to Lever's Privacy Notice and Cookie Policy, which governs the processing of visitor data on this platform.

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