Ingersoll Rand is committed to achieving workforce diversity reflective of our communities. We are an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.

Job Summary

The Business Intelligence and Data Analytics team is in search of a Data Scientist to help us achieve our mission of enabling actionable insights throughout Ingersoll Rand to increase revenue, improve productivity, and better serve our customers. We are transforming the organization by creating streamlined, sustainable, and maintainable data infrastructure and systems. We strive to enable analysts in the business to create insights and to build a single source of data truth that is trusted, dependable, and available.

Reporting to the Director, Data Science and Data Strategy, this role will work with businesses to solve meaningful problems by modeling, analyzing, and understanding outputs to deliver insights, predict emerging trends, and provide recommendations to deliver exponential results. This role will collaborate with the entire Business Intelligence & Data Analytics team, including, data engineers, data architects and business analysts. This role will also collaborate directly with Business Functions to bring solutions to their data needs, such as Machine Learning Models and dashboards they can use to interpret and action the results.

The ideal candidate loves data, can apply algorithms, and build impactful visualizations. They blend math, developer skills, and an understanding of business to find compelling answers to meaningful questions in data. They have a passion for using data to solve problems and enjoy keeping up-to-date with the latest technologies.

Specific Responsibilities:

1. **Data Exploration and Analysis:**
- Conduct exploratory data analysis (EDA) to identify trends, patterns, and anomalies in large data sets.
- Use statistical methods to analyze data and generate actionable insights.
- Perform data cleaning, transformation, and feature engineering to prepare data for modeling.

2. **Model Development:**
- Develop and implement machine learning models and algorithms to solve business problems.
- Validate and evaluate model performance using appropriate metrics and techniques.
- Iterate on models to improve accuracy and effectiveness.

3. **Big Data and Analytics:**
- Work with big data technologies (e.g., Hadoop, Spark) to process and analyze large data sets.
- Utilize advanced analytics techniques (e.g., clustering, classification, regression) to derive insights.
- Leverage cloud platforms (e.g., AWS, Azure, Google Cloud) for scalable data processing and analysis.

4. **Visualization and Reporting:**
- Create visualizations and dashboards to effectively communicate findings to stakeholders.
- Develop reports and presentations to summarize insights and recommendations.
- Collaborate with data visualization experts to design user-friendly interfaces.

5. **Collaboration and Communication:**
- Work closely with cross-functional teams, including data engineers, analysts, and business stakeholders, to understand data needs and deliver solutions.
- Participate in agile development processes, including sprint planning, daily stand-ups, and retrospectives.
- Communicate complex technical concepts to non-technical audiences.

6. **Research and Innovation:**
- Stay updated with the latest developments in data science, machine learning, and AI.
- Continuously evaluate and adopt new tools and techniques to enhance data science capabilities.
- Promote a culture of innovation and continuous improvement within the team.

7. **Data Governance and Security:**
- Ensure data security and compliance with relevant regulations and standards.
- Implement best practices for data governance and data quality.
- Maintain comprehensive documentation of data science processes, models, and code.

Required Qualifications:

• Bachelor's (or higher) degree in data science, Computer Science, Statistics, Mathematics, or a related field.
• 3+ years of experience in data science, machine learning, or a similar role
• Proficiency in programming languages such as Python or R.
• Strong knowledge of machine learning frameworks and libraries (e.g., Jupyter Notebooks, SnowPark)
• Experience with data visualization tools (e.g., Qlik, Excel, PowerPoint)
• Familiarity with big data technologies (e.g., Snowflake, Qlik Data Integration, Qlik Data
• Analytics) and cloud platforms (e.g., AWS, Azure, Google Cloud).
• Excellent analytical, problem-solving, and communication skills.
• Ability to work effectively in a fast paced, dynamic environment.

Preferred Qualifications:

• Demonstrated coding proficiency with SQL, Python, R
• Experience of Qlik scripting language
• 5+ years in data analytics / data science in a fast-paced, complex environment
• Experience working with Snowflake data cloud
• Experience with demand generation data and concepts
• Experience with VBA, Access, Salesforce and other BI tools
• Knowledge of sales processes and commercial data flow a plus

Ingersoll Rand Inc. (NYSE:IR), driven by an entrepreneurial spirit and ownership mindset, is dedicated to helping make life better for our employees, customers and communities. Customers lean on us for our technology-driven excellence in mission-critical flow creation and industrial solutions across 40+ respected brands where our products and services excel in the most complex and harsh conditions. Our employees develop customers for life through their daily commitment to expertise, productivity and efficiency. For more information, visit www.IRCO.com.