Mgr, Data Sci & Analytics

Job description

**Role:** Mgr, Data Sci & Analytics **Location:** Bangalore **Full/ Part-time:** Full time **About Carrier** Carrier Global Corporation, global leader in intelligent climate and energy solutions, is committed to creating innovations that bring comfort,safetyand sustainability to life. Throughcutting-edgeadvancements in climate solutions such as temperature control, airqualityand transportation, we improve lives, empower criticalindustriesand ensure safe transport of food, life-saving medicines and more. Since inventing modern air conditioning in 1902, we lead with purpose: enhancing the lives we live and the world we share. We continue to lead because of our world-class, inclusive workforce that puts the customer at thecentreofeverything we do. For more information, visitcorporate.carrier.com (opens in new window)or follow Carrier on social media at @Carrier. **About This Role** We are seeking an experienced **AI / Analytics Engineer** to join Carrier’s Global Data, Analytics & AI organization. This role is ideal for a hands-on engineer who combines a **strong analytics foundation** with **modern AI/ML, GenAI, and Agentic AI engineering experience** to develop scalable, business-critical solutions. The AI / Analytics Engineer will work closely with business stakeholders, product managers, and platform teams to **understand business problems** , translate them into **data- and AI-driven solutions** , and deliver production-ready capabilities that create measurable business value. This role requires an **entrepreneurial mindset** , the ability to **move quickly from idea to solution** , and a strong focus on building solutions that **scale across functions, regions, and use cases** . **Key Responsibilities** **Solution Development & Engineering** - Design, develop, and deploy analytics, AI/ML, GenAI, and Agentic AI solutions that address real business problems across functions such as Supply Chain, Manufacturing, Service, Marketing, and Commercial Operations. - Build and maintain analytics engineering pipelines (data ingestion, transformation, semantic layers, feature engineering) to support advanced analytics and AI use cases. - Develop and operationalize machine learning models (predictive, prescriptive, optimization) and GenAI solutions (e.g., RAG-based assistants, summarization, Q&A, copilots). - Design and implement Agentic AI workflows that orchestrate tools, data, and models to automate multi-step business processes with appropriate guardrails and human-in-the-loop controls. **Business Understanding & Problem Solving** - Partner with business stakeholders and product teams to understand requirements, frame problems, and identify opportunities where analytics and AI can drive impact. - Translate ambiguous business needs into clear technical designs, data requirements, and solution architectures. - Apply strong analytical thinking to define success metrics, validate assumptions, and continuously improve solutions based on outcomes. **Platform, Scale & Operations** - Collaborate with data platform, architecture, and security teams to ensure solutions align with enterprise standards, governance, and scalability requirements. - Optimize models and pipelines for performance, reliability, cost, and scalability. - Support production deployment and monitoring of analytics and AI solutions, including model performance, data quality, and system reliability. - Contribute to best practices for MLOps / LLMOps, including versioning, testing, evaluation, and monitoring. **Innovation & Continuous Improvement** - Stay current with emerging trends in AI/ML, GenAI, Agentic AI, and analytics engineering, and proactively evaluate how new technologies can be applied at Carrier. - Experiment, prototype, and iterate quickly—while designing solutions that can be scaled and reused across the enterprise. - Promote responsible and ethical AI practices, including bias mitigation, transparency, and regulatory compliance. **Required Qualifications** - Bachelor’s degree in Computer Science, Data Science, Engineering, Business Analytics, or a related field. - 5–10 years of relevant experience in analytics engineering, data engineering, AI/ML engineering, or advanced analytics roles. - Strong experience working with data analytics, data modeling, and large datasets in enterprise environments. - Hands-on experience developing and deploying AI/ML models and analytics solutions. - Proficiency in Python, SQL, and modern analytics or ML frameworks. - Experience collaborating with business stakeholders and cross-functional teams. **Preferred Qualifications** - Hands-on experience with GenAI (e.g., RAG architectures, prompt engineering, LLM integration, evaluation frameworks). - Exposure to or experience building Agentic AI solutions (tool-using agents, workflow orchestration, automation). - Experience with modern data and analytics platforms such as Snowflake, Databricks, and visualization tools like Power BI. - Familiarity with cloud platforms (AWS, Azure, or GCP). - Experience applying Agile / product-oriented delivery models. - Background in manufacturing, industrial, or HVAC domains is a plus. **Success Profile** - Problem solver with a strong analytical mindset and curiosity. - Entrepreneurial and action-oriented, comfortable working in ambiguity and moving quickly. - Engineering discipline with scale in mind—builds solutions that last. - Strong collaborator who can bridge business needs and technical execution. - Passionate about using data and AI to drive meaningful outcomes. **Benefits** We offer a competitive total rewards package that may include other benefits andwell‑beingprograms. Offerings vary by role and location and are designed to support employees’ health, security, and success. **Equal Treatment and Non-Discrimination** Carrier is committed to equal treatment and non-discrimination principles. All qualified applicants will receive consideration for