Senior Director, Data Science

Dun & Bradstreet unlocks the power of data through analytics, creating a better tomorrow. Each day, we are finding new ways to strengthen our award-winning culture and accelerate creativity, innovation and growth. Our 6,500+ global team members are passionate about what we do. We are dedicated to helping clients turn uncertainty into confidence, risk into opportunity and potential into prosperity. Bold and diverse thinkers are always welcome. Come join us Learn more at dnb.com/careers.

We are seeking an exceptional Senior Director, Data Science with a proven history of leading teams through complete model operations and implementations at the intersection of analytics, technology, product, and business.

The Senior Director, Data Science role involves acting as a bridge between multiple stakeholders, including Sales, Statistical Modeling, Technology, Product Owners, and D&B's external clients.

The ideal Senior Director, Data Science is a self-motivated individual who will drive all assigned projects forward, ensuring the delivery of top-notch, data-driven analytics solutions to our customers.

Success in this role requires excelling at tackling various business challenges through the application of diverse tools, strategies, algorithms, and programming languages.

We are a team dedicated to supporting and respecting each other, where success is defined by what's best for our customers, colleagues, and Dun & Bradstreet.

Key Responsibilities

• Technical Collaboration
• Collaborate across Data Science during the model / Insight building process on best practices prior implementation for all D&B Standard and Custom Scores.
• Collaborate closely with data scientists, technology software engineers, and DevOps teams to streamline the machine learning and LLM powered application lifecycles and optimize AI application performance.
• Thought leadership / tool recommendations for efficiency within the data science function.
• Though leadership and mentoring our Chennai Analytics teams in new methodologies and best practices within Implementations and Monitoring.
• Support Risk, S&MS, Public Sector, Capital Market and GenAi Apps Solutions.

• GenAI Observability & monitoring
• Ability to partner with D&B Data Science and Technology and become a key thought leader, as we continue evolving our GenAI observability & monitoring.
• The individual should be able to quickly get up-to-speed on numerous frameworks and software applications, both from the data governance and technical implementation perspectives.
• Exceptional interpersonal skills and demonstrated ability to build rapport with senior stakeholders across Technology, Data Science, Data Governance, Cybersecurity, and Product.
• Comfort with highly technical environments, such as data warehousing, enterprise architecture and software implementations.
• Strong demonstrated experience of driving data engineering performed on very large and diverse datasets, both structured and unstructured.
• Strong capacity planning, sizing and budgeting skills.

• Capital Markets Operations
• Ability to lead data engineering and architecture design for analytics platforms in support of Capital Markets customer-facing initiatives.
• Demonstrated commitment to exceptional customer service in fast-paced and demanding environments and ability to build relationships based on trust and credibility with senior stakeholders.
• Exceptionally strong ability to support custom analytic delivery as necessary and standardize / modernize legacy custom processes.

• MLOps
• Collaborate with data scientists to understand model requirements and deployment constraints.
• Partner with technology teams to design and develop an MLOps architecture that progressively achieves optimal maturity.
• Collaborate with technology and recommend scalable and reliable processes to handle model inference at scale.
• Collaborate with technology to develop containerization and orchestration solutions for model deployment.

• Collaborate with Technology
• Collaborate with technology partners to develop and maintain automated pipelines for model training, testing, and deployment.
• Collaborate with technology partners and champion CI/CD practices to facilitate rapid and reliable model updates.

• Best Practice Model Reviews, Validations and Product Consumption.
• Model review, refactoring, and optimization.
• Models testing, validation and tests automation.
• Champion and collaborate with product on ingesting new scores seamlessly requiring minimal product intervention.
• Enhance Data Presentation: Utilize visual tools such as ESRI software, Power BI, and Tableau to drive dashboard creation and data visualization.

• Other day-day Activities
• Code and test end- to- end Scorecard or Machine Learning model data preparation and scoring flow including model pre and post processing rules (Availability, Override rules).
• Code and test model reason codes logic and create reason commentaries, if applicable.
• Validate the input data element mappings (model development vs production) and perform thorough data input flow test.
• Document Model Technical Specifications.
• Work with Technology Quality Assurance teams to prepare test data and execute scoring engine and model UAT tests.
• Perform post-implementation QA and review audit reports.
• Create audit triggers script for the model input attributes and output score to enable automated model audit and monitoring capability.
• Work with technology partners to create retro scoring capabilities post model implementation.
• Post Implementation support for any inquiries related to the deployed models.
• Automate batch manual jobs to improve the operation efficiency.
• Perform various data collection, predictive analysis and processing on Analytics Data/Score Assets using advanced statistical tools for various custom projects.

Qualifications

• A graduate degree in a quantitative or applied field, such as Computer Science or Engineering, or equivalent experience in Statistics, Operations Research, Mathematics, or related areas with relevant experience.
• Strong data analytics experience with hands-on programming skills in Python, PySpark, R, Java, SQL (10+ years of experience)
• Knowledge of LLM powered application lifecycle (LangSmith) is a major plus.
• Experience building CI/CD pipelines orchestration using GitHub Actions, Airflow etc.
• Machine Learning and embeddings, Databricks and cloud-based platforms experience is required.
• Experience with ML Ops best practice.
• Data science model review, run the code refactoring and optimization, containerization, deployment, versioning.
• Experience testing sophisticated GenAi apps is a big plus.
• Strong analytical skill with statistical modeling background is required.
• Strong testing skills - experience in a Quality Assurance organization is highly desirable.
• High level of experience using visualization tools ArcGIS is highly desirable.
• Proven track record of independent thinking & ingenuous approaches to problem solving.
• Ability to brainstorm, exchange, encourage ideas and mentoring in a team environment.
• Ability to demonstrate effective communication and project management skills.

Benefits We Offer

· Generous paid time off in your first year, increasing with tenure.

· Up to 16 weeks 100% paid parental leave after one year of employment.

· Paid sick time to care for yourself or family members.

· Education assistance and extensive training resources.

· Do Good Program: Paid volunteer days & donation matching.

· Competitive 401k & Employee Stock Purchase Plan with company matching.

· Health & wellness benefits, including discounted Wellhub membership rates.

· Medical, dental & vision insurance for you, spouse/partner & dependents.

· Learn more about our benefits: .

All Dun & Bradstreet job postings can be found at and . Official communication from Dun & Bradstreet will come from an email address ending in @dnb.com.

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