Burns & McDonnell-posted 3 months ago
Appleton, WI
Professional, Scientific, and Technical Services

The Staff Data Scientist plays a critical role in leveraging data to drive business insights, optimize operations, and support strategic decision-making. You will be responsible for designing and implementing advanced analytical models, developing data pipelines, and applying statistical and machine learning techniques to solve complex business challenges. This position requires a balance of technical expertise, business acumen, and communication skills to translate data findings into actionable recommendations.

  • Develop and apply data solutions for cleansing data to remove errors and review consistency.
  • Perform analysis of data to discover information, business value, patterns and trends in support to guide development of asset business solutions.
  • Gather data, find patterns and relationships and create prediction models to evaluate client assets.
  • Conduct research and apply existing data science methods to business line problems.
  • Monitor client assets and perform predictive and root cause analysis to identify adverse trends; choose best fit methods, define algorithms, and validate and deploy models to achieve desired results.
  • Produce reports and visualizations to communicate technical results and interpretation of trends; effectively communicate findings and recommendations to all areas of the business.
  • Collaborate with cross-functional stakeholders to assess needs, provide assistance and resolve problems.
  • Translate business problems into data science solutions.
  • Performs other duties as assigned.
  • Complies with all policies and standards.
  • Bachelor Degree in Analytics, Computer Science, Information Systems, Statistics, Math, or related field from an accredited program and 4 years related experience required or experience may be substituted for degree requirement required.
  • Experience in data mining and predictive analytics.
  • Strong problem-solving skills, analytical thinking, attention to detail and hypothesis-driven approach.
  • Excellent verbal/written communication, and the ability to present and explain technical concepts to business audiences.
  • Proficiency with data visualization tools (Power BI, Tableau, or Python libraries).
  • Experience with Azure Machine Learning, Databricks, or similar ML platforms.
  • Expert proficiency in Python with pandas, scikit-learn, and statistical libraries.
  • Advanced SQL skills and experience with large datasets.
  • Experience with predictive modeling, time series analysis, and statistical inference.
  • Knowledge of A/B testing, experimental design, and causal inference.
  • Familiarity with computer vision for image/video analysis.
  • Understanding of NLP techniques for document processing.
  • Experience with optimization algorithms and operations research techniques preferred.
  • Knowledge of machine learning algorithms, feature engineering, and model evaluation.
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