Principal, Data Scientist
dun bradstreet
Job Summary
As a Principal Data Scientist on the Data & Analytics team, you will be involved in all aspects of modeling engagements. This includes design, development, validation, calibration, documentation, approval, implementation, monitoring, and reporting. You will research complex business issues and recommend solutions, including model features, end products, and necessary data to support Dun & Bradstreet's growing initiatives. Key responsibilities involve developing global analytic solutions using statistical models, creating and validating features with diverse data sources, and applying machine learning techniques such as Natural Language Processing. You will also maintain stakeholder relationships, act as a subject matter expert, share best practices, and build relationships with external data vendors. The role requires a strategic mindset with an execution focus, a continuous growth mindset, and an ownership mentality.
Must Have
- 12+ years of data science experience
- Proficiency in Python, Spark, PySpark, PyTorch, SQL
- Knowledge of data science concepts (big data, NLP, feature engineering)
- Working knowledge of diverse data formats
- Strategic and execution mindset
- Microsoft Office Suite proficiency
- Continuous growth mindset
- Ownership mindset
- Problem-solving skills
- Proactive and collaborative approach
Good to Have
- Master's Degree or Ph.D. in a quantitative field (Statistics, Computer Science, etc.)
- Fluency in languages relevant to the working market
Perks & Benefits
- Generous paid time off
- 100% paid parental leave
- Paid sick time
- Education assistance and training resources
- Paid volunteer days and donation matching
- Competitive 401k with company matching
- Health & wellness benefits
- Medical, dental & vision insurance
Job Description
Key Responsibilities:
- Develop Global Analytic Solutions inclusive but not limited to statistical models based on D&B’s established best practices, methodologies, and tools.
- Research complex business issues and recommend solutions, including model features and end products.
- Create features and validate them against diverse set of objectives utilizing both internal and external data sources while maintaining business relationships and serving as subject matter expert.
- Utilize latest data science techniques across both supervised and unsupervised machine learning methodologies, Natural Language Processing in automating and scaling internal business processes and development of new capabilities for the business.
- 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.
- Share academic literature and industry best practices. 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.
- 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.
- Search for new alternative data based on the use cases - customer problems by business units, data quality and additional product needs.
Skills and/or Certifications:
- 12+ years of relevant experience in data science roles.
- Proficiency utilizing Python, Spark, PySpark, PyTorch and SQL.
- Knowledge of evolving data science concepts and best practices including big data, NLP, feature engineering, regressive and non-regressive methods, and unstructured data synthesis.
- Working knowledge with diverse data formats and data structures.
- 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.
- Proficiency in Microsoft Office Suite skills.
- 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.
- 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
Education:
- Master’s Degree or Ph.D. in a quantitative/applied field preferred (Statistics, Econometrics, Computer Science, Operations Research, Mathematics, Engineering)
- Bachelors degree - Required
- Advanced degree - Preferred