Data Scientist

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 Title

Data Scientist – MLOps & Analytics Governance

Location

Bangalore

About Us

Ingersoll Rand is a global provider of mission-critical flow creation, life science and industrial solutions. Ingersoll Rand’s Global Engineering & Technology Center (GEC) in Bangalore, A GREAT PLACE TO WORK CERTIFIED WORKPLACE is driven by an ownership mindset and entrepreneurial spirit, has been a beacon of innovation for over 19 years, embodying our purpose to “Make Life Better” for our employees, customers, shareholders and the planet.

The Engineering & Technology center has expertly supported a diverse range of industrial products, offering deep expertise in core and digital engineering space. By cultivating a sense of inclusion, belonging and respect, and a collaborative culture, the GEC has fostered the most talented and capable engineers, thereby playing a pivotal role in driving Ingersoll Rand’s purpose and strategic focus areas.

Job & Division Summary:

We are looking for a technically strong Data Scientist – MLOps & Analytics Governance with 4–5 years of experience who will own the full MLOps lifecycle, enforce data quality governance and insights validations. The ideal candidate is highly proficient in writing optimised, scalable Python and SQL code with deep hands-on experience running large-scale workloads in BigQuery on GCP. This role is critical to ensuring ML models are deployed reliably in cloud and that all insights reaching stakeholders are statistically sound and validated. The candidate is expected to actively leverage Generative AI tools (such as GitHub Copilot, Claude, or equivalent LLM-based assistants) to accelerate software development, automate repetitive coding tasks, and improve overall engineering productivity. Domain exposure to manufacturing, IoT analytics, or rotating equipment such as air compressors is a strong advantage.