Data Scientist

Job Purpose

Leveraging advanced analytical techniques, statistical modeling, and/or machine learning, you will partner with the business to uncover opportunities, optimize performance, and drive data-informed outcomes.

About the Role

This role combines advanced data science techniques with business partnership to identify opportunities, solve complex problems, and generate insights for decision support. The ideal candidate combines strong technical expertise in statistical modeling and advanced analytics with the ability to translate complex data into clear, business-relevant insights for marketing and sales teams.

Responsibilities

• Complete end-to-end data science initiatives, from business problem framing and data exploration through model development, validation, deployment partnership, and performance monitoring.
• Work directly with internal and external customers to define success criteria, hypotheses, and measurable outcomes. Translate the business needs into analytics/reporting requirements to support executive decisions and workflows with required information.
• Design, build, and evaluate predictive, prescriptive, and statistical models that improve decision-making, operational efficiency, customer outcomes, or financial performance.
• Design and evaluate experiments to test hypotheses, measure impact, and guide decisions (e.g., A/B, Multivariate, simulation, scenario, Quasi, etc.).
• Apply advanced analytical methods such as machine learning, forecasting, optimization, causal inference, and experimentation to solve high-value business problems.
• Proactively identify trends and patterns and generate insights for business units and senior leadership.
• Work with the IT Data Engineering team to integrate data from multiple sources including CRM, ERP, Operational systems, web analytics, and third-party datasets for analysis.
• Research and implement cutting-edge techniques and tools in machine learning/artificial intelligence to make data analysis more efficient.
• Present insights and recommendations to stakeholders in a clear, business-focused manner. Simplify complex methodologies into actionable business insights.
• Establish processes and tools that monitor, analyze, and continuously improve model performance and data accuracy.
• Partner with the Analytics leadership team to align initiatives and strategy. Contribute to enterprise analytics roadmap and best practices.
• Support other Analytics team members by providing technical guidance, peer review, and thought partnership.

Requirements

• 5+ years of progressive experience in data science, advanced analytics, or a closely related field, with a strong preference supporting marketing or commercial teams.
• Experience in the development of Machine Learning models and AI frameworks.
• Experience working with data visualization and business intelligence tools to communicate insights effectively. (e.g., Tableau, Power BI, or similar tools)
• Experience working with enterprise data platforms (e.g., Snowflake, Databricks, Cloudera, BigQuery)
• Experience working with data from large enterprise applications (eERP, CRM or Operational systems)
• Preferred experience working with SAP (S/4 HANA, ECC, BTP, etc.)
• Preferred experience working with Cloud platforms (AWS, Azure, or GCP)
• Preferred experience in text analytics, image recognition, graph analysis, or other specialized ML techniques, such as deep learning
• Preferred experience in manufacturing, building products, or construction-related industries.
• Fluency in multiple analytical programming languages such as Python & SQL (required), R (optional)
• Demonstrated experience developing and validating statistical models, machine learning algorithms, and advanced analytical solutions using large, complex datasets.
• Strong competency in Statistical & Quantitative Methods (e.g., Hypothesis testing, regression, probability theory, experimental design etc)
• Demonstrated experience and comfortable with experimentation and causal analysis.
• Demonstrated experience with experimental design, model evaluation, and performance measurement.
• Strong understanding of data pipelines, ETL processes, and data architecture
• Proven success in supervised and unsupervised learning (e.g., regression, classification, clustering)
• Strong understanding of AI, its potential roles in solving business problems, and the future trajectory of generative AI models
• Excellent presentation, communication and stakeholder management skills, with the ability to explain technical concepts in business terms to a diverse audience with a wide range of understanding
• Highly self-motivated with proven ability to operate autonomously. Manage multiple priorities, in a fast-paced environment
• Willingness and ability to learn new technologies on the job with a continuous learning and innovation mindset

Qualifications

• Bachelor’s degree in computer science, mathematics, data science, statistics, or a related quantitative field.
• Master’s degree preferred.

Benefits

In this position you will have the opportunity to:

• Complete end-to-end data science initiatives, from business problem framing and data exploration through model development, validation, deployment partnership, and performance monitoring.
• Work directly with internal and external customers to define success criteria, hypotheses, and measurable outcomes. Translate the business needs into analytics/reporting requirements to support executive decisions and workflows with required information.
• Design, build, and evaluate predictive, prescriptive, and statistical models that improve decision-making, operational efficiency, customer outcomes, or financial performance.
• Design and evaluate experiments to test hypotheses, measure impact, and guide decisions (e.g., A/B, Multivariate, simulation, scenario, Quasi, etc.).
• Apply advanced analytical methods such as machine learning, forecasting, optimization, causal inference, and experimentation to solve high-value business problems.
• Proactively identify trends and patterns and generate insights for business units and senior leadership.
• Work with the IT Data Engineering team to integrate data from multiple sources including CRM, ERP, Operational systems, web analytics, and third-party datasets for analysis.
• Research and implement cutting-edge techniques and tools in machine learning/artificial intelligence to make data analysis more efficient.
• Present insights and recommendations to stakeholders in a clear, business-focused manner. Simplify complex methodologies into actionable business insights.
• Establish processes and tools that monitor, analyze, and continuously improve model performance and data accuracy.
• Partner with the Analytics leadership team to align initiatives and strategy. Contribute to enterprise analytics roadmap and best practices.
• Support other Analytics team members by providing technical guidance, peer review, and thought partnership.

Skills

• Advanced analytical techniques, statistical modeling, and machine learning.
• Data visualization and business intelligence tools.
• Enterprise data platforms and large, complex datasets.
• Machine learning, forecasting, optimization, causal inference, and experimentation.
• Text analytics, image recognition, graph analysis, or other specialized ML techniques.
• Manufacturing, building products, or construction-related industries.
• Multiple analytical programming languages such as Python & SQL.
• Statistical & Quantitative Methods.
• Experimentation and causal analysis.
• Experimental design, model evaluation, and performance measurement.
• Data pipelines, ETL processes, and data architecture.
• Supervised and unsupervised learning.
• AI, generative AI models, and continuous learning.
• Presentation, communication, and stakeholder management skills.
• Self-motivation and ability to operate autonomously.
• Continuous learning and innovation mindset.

Pay

Negotiable based on experience and qualifications.

Schedule

Full-time position.