Sr. Data Scientist

Baker Group•Ankeny, IA

33d

About The Position

The Sr. Data Scientist is responsible for extracting insights from data across multiple business units and departments using advanced analytics, statistical modeling, and machine learning techniques. This role will analyze complex datasets, develop predictive models, and make strategic data-design decisions to support business decision-making. The Data Scientist will collaborate with business leaders, the software development team and field & shop operations to identify opportunities for data-driven improvements, develop scalable analytical solutions, and maintain data infrastructure. This position reports to the Software Development Team Leader and will work closely with stakeholders across Baker Group.

Requirements

Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, or other relevant quantitative field
5 years or more experience in data science, analytics, or related field
Proficiency with statistical programming languages such as Python or R
Experience with SQL and database technologies for data extraction and manipulation
Experience with Microsoft Fabric, ETL processes & medallion architecture best practices
Experience with data visualization tools such as PowerBI, Tableau, or similar platforms
Proven ability to work with large datasets and implement scalable analytical solutions
Demonstrated experience with machine learning frameworks and libraries (e.g., scikit-learn, TensorFlow, PyTorch)
Strong understanding of statistical methods, experimental design, and predictive modeling techniques
Strong analytical and critical thinking skills with ability to translate complex data into actionable business insights
Excellent time and project management skills with capability to prioritize and multitask across multiple analytical projects
Current with industry trends in data science, machine learning, and best practices with ability to identify ones we should implement
Exceptional troubleshooting and problem-solving skills with the ability to spot data quality issues and model performance problems before they impact business decisions
Strong communication skills with ability to present technical findings to non-technical audiences
Team player with strong collaboration skills and customer service orientation
Must be able to focus on complex analytical problems and work independently with minimal supervision
Ability to work in a fast-paced environment and adapt to changing business priorities
Meticulous attention to detail and commitment to producing high-quality, accurate analytical work

Nice To Haves

Master's degree in relevant field is a plus, but not a requirement
Well-developed business acumen and understanding of day-to-day business functions in construction or related industries is a plus
No specific requirements; however, relevant certifications in data science, machine learning, or cloud platforms (Azure or Google Cloud) are a plus

Responsibilities

Analyzes statistics and information from multiple data sources to extract meaningful insights and identify trends that give the company a competitive advantage.
Develops and implements statistical modeling frameworks, experiment designs, and tests to validate predictive models.
Builds and deploys machine learning models for forecasting, classification, and optimization across business operations.
Conducts scalable research and analysis on and off the cloud to support data-driven decision making.
Creates compelling data visualizations and dashboards that effectively communicate complex insights to technical and non-technical audiences.
Collaborates with business stakeholders to understand requirements, develop data-design strategies, and determine what insights are most valuable.
Designs and implements statistical and machine learning approaches to analyze construction data including labor tracking, project performance, and resource allocation.
Develops, refines, and scales data management and analytics platforms that enable efficient data processing for predictive modeling.
Develops and maintains data pipelines and ETL processes to ensure data quality and availability.
Produces and maintains comprehensive documentation on data models, analytical methodologies, and findings.
Conducts quality assurance on data analysis outputs to ensure accuracy and reliability of insights.
Researches and resolves data quality issues discovered in analysis reviews.
Monitors key performance metrics for data infrastructure and analytical model performance.
Maintains knowledge of emerging trends in data science, machine learning, and analytics tools and recommends relevant updates to management.
Consults with management to determine future analytical requirements for upcoming projects and strategic initiatives.
Supports business units with relevant data science needs including predictive analytics, optimization, and business intelligence.
Stays current by researching new analytical techniques, tools, frameworks, and relevant solutions that will bring additional value to the organization.