Data Science Intern - Summer 2027

Are you interested in applying data science to real business and product challenges? As a Data Science Intern at Resideo, you will work alongside data scientists, engineers, and business stakeholders to explore data, develop analytical solutions, and communicate actionable insights. You will gain hands-on experience with Python, SQL, and Databricks while supporting data preparation, visualization, and predictive modeling. With guidance from the team, you will complete a scoped project and present your findings and recommendations. Help create innovative technologies that make the world cleaner and more sustainable, more secure, connected, energy efficient, and productive. JOB DUTIES: • Explore and analyze data to identify trends, patterns, and opportunities for business or product improvement. • Clean and prepare datasets, addressing missing values, inconsistencies, and data quality issues. • Write SQL queries and Python scripts in Databricks to extract, transform, and analyze data from multiple sources. • Develop Databricks notebooks, dashboards and visualizations to communicate key findings and track performance metrics. • Support predictive modeling, including feature development, model training, and performance evaluation. • Analyze product usage and performance to understand customer behavior and identify opportunities for improvement. • Automate recurring analyses and reports to reduce manual effort and improve consistency. • Collaborate with data scientists, engineers, and business stakeholders to translate business questions into analytical tasks. • Document datasets, methods, code, and findings using team standards and Git workflows. • Complete and present a scoped capstone project, explaining the approach, results, limitations, and recommended next steps.

Are you interested in applying data science to real business and product challenges? As a Data Science Intern at Resideo, you will work alongside data scientists, engineers, and business stakeholders to explore data, develop analytical solutions, and communicate actionable insights. You will gain hands-on experience with Python, SQL, and Databricks while supporting data preparation, visualization, and predictive modeling. With guidance from the team, you will complete a scoped project and present your findings and recommendations. Help create innovative technologies that make the world cleaner and more sustainable, more secure, connected, energy efficient, and productive. JOB DUTIES: • Explore and analyze data to identify trends, patterns, and opportunities for business or product improvement. • Clean and prepare datasets, addressing missing values, inconsistencies, and data quality issues. • Write SQL queries and Python scripts in Databricks to extract, transform, and analyze data from multiple sources. • Develop Databricks notebooks, dashboards and visualizations to communicate key findings and track performance metrics. • Support predictive modeling, including feature development, model training, and performance evaluation. • Analyze product usage and performance to understand customer behavior and identify opportunities for improvement. • Automate recurring analyses and reports to reduce manual effort and improve consistency. • Collaborate with data scientists, engineers, and business stakeholders to translate business questions into analytical tasks. • Document datasets, methods, code, and findings using team standards and Git workflows. • Complete and present a scoped capstone project, explaining the approach, results, limitations, and recommended next steps. YOU MUST HAVE: • Active student status pursuing a degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. • Foundational experience with Python and SQL through coursework, academic projects, or internships. • Basic understanding of statistics, data analysis, and machine learning concepts.

JOB DUTIES: • Explore and analyze data to identify trends, patterns, and opportunities for business or product improvement. • Clean and prepare datasets, addressing missing values, inconsistencies, and data quality issues. • Write SQL queries and Python scripts in Databricks to extract, transform, and analyze data from multiple sources. • Develop Databricks notebooks, dashboards and visualizations to communicate key findings and track performance metrics. • Support predictive modeling, including feature development, model training, and performance evaluation. • Analyze product usage and performance to understand customer behavior and identify opportunities for improvement. • Automate recurring analyses and reports to reduce manual effort and improve consistency. • Collaborate with data scientists, engineers, and business stakeholders to translate business questions into analytical tasks. • Document datasets, methods, code, and findings using team standards and Git workflows. • Complete and present a scoped capstone project, explaining the approach, results, limitations, and recommended next steps. YOU MUST HAVE: • Active student status pursuing a degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. • Foundational experience with Python and SQL through coursework, academic projects, or internships. • Basic understanding of statistics, data analysis, and machine learning concepts. WE VALUE: • Ability to communicate findings clearly, collaborate with others, and explain analytical work to technical and nontechnical audiences. • Experience cleaning, exploring, and visualizing data through coursework, research, or personal projects. • Familiarity with Databricks, Apache Spark, or cloud data platforms, and an interest in learning these tools. • Exposure to Python libraries such as pandas, NumPy, scikit-learn, or Matplotlib, and to Git for version control. • Curiosity, attention to data quality, and the ability to break practical problems into manageable analytical tasks. • Willingness to learn from feedback, document work, and collaborate with data scientists, engineers, and business stakeholders.

YOU MUST HAVE: • Active student status pursuing a degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. • Foundational experience with Python and SQL through coursework, academic projects, or internships. • Basic understanding of statistics, data analysis, and machine learning concepts. WE VALUE: • Ability to communicate findings clearly, collaborate with others, and explain analytical work to technical and nontechnical audiences. • Experience cleaning, exploring, and visualizing data through coursework, research, or personal projects. • Familiarity with Databricks, Apache Spark, or cloud data platforms, and an interest in learning these tools. • Exposure to Python libraries such as pandas, NumPy, scikit-learn, or Matplotlib, and to Git for version control. • Curiosity, attention to data quality, and the ability to break practical problems into manageable analytical tasks. • Willingness to learn from feedback, document work, and collaborate with data scientists, engineers, and business stakeholders. WHAT'S IN IT FOR YOU: • Hands-on experience: Apply Python, SQL, and Databricks to real business and product data. • Mentorship and collaboration: Learn from experienced data scientists and engineers while contributing to meaningful projects. • Professional development: Build data science skills and present a capstone project with clear results, limitations, and recommendations.

WE VALUE: • Ability to communicate findings clearly, collaborate with others, and explain analytical work to technical and nontechnical audiences. • Experience cleaning, exploring, and visualizing data through coursework, research, or personal projects. • Familiarity with Databricks, Apache Spark, or cloud data platforms, and an interest in learning these tools. • Exposure to Python libraries such as pandas, NumPy, scikit-learn, or Matplotlib, and to Git for version control. • Curiosity, attention to data quality, and the ability to break practical problems into manageable analytical tasks. • Willingness to learn from feedback, document work, and collaborate with data scientists, engineers, and business stakeholders. WHAT'S IN IT FOR YOU: • Hands-on experience: Apply Python, SQL, and Databricks to real business and product data. • Mentorship and collaboration: Learn from experienced data scientists and engineers while contributing to meaningful projects. • Professional development: Build data science skills and present a capstone project with clear results, limitations, and recommendations. #LI-Hybrid