Senior Data Scientist

About Us

Automation Anywhere is the leader in Agentic Process Automation (APA), transforming how work gets done with AI-powered automation. Its APA system, built on the industry’s first Process Reasoning Engine (PRE) and specialized AI agents, combines process discovery, RPA, end-to-end orchestration, document processing, and analytics—all delivered with enterprise-grade security and governance. Guided by its vision to fuel the future of work, Automation Anywhere helps organizations worldwide boost productivity, accelerate growth, and unleash human potential.

Job Description :
Our opportunity
Automation Anywhere is the leader in Agentic Process Automation (APA), redefining how enterprises automate and scale work through AI-powered automation. Our AI-native APA platform combines advanced AI agents, machine learning, orchestration, and enterprise-grade automation to help organizations unlock productivity, accelerate innovation, and build the Autonomous Enterprise. As we continue to push the boundaries of AI and intelligent automation, we are looking for exceptional AI/ML talent to help shape the future of enterprise AI. Role : Senior Data Scientist EngineerLocation : Bangalore (Onsite)
Join our Product-building AI/ML team where you’ll have the opportunity to lead cutting-edge AI and machine learning research initiatives while continuing to grow as a hands-on software engineer. This role offers the unique chance to drive ML innovation from concept to production — influencing research direction, developing scalable ML systems, and bringing advanced AI capabilities into real-world enterprise products. If you’re passionate about solving complex problems, translating research into impactful applications, and accelerating your technical growth in a fast-moving AI environment, we’d love to meet you. Who you’ll report to:
This role reports to our Sr. Director, Engineering You will make an impact by being responsible for:·       Building and deploying production ML systems from prototype through to production·       Improving the reliability, accuracy, and maintainability of production ML services·       Designing and implementing novel ML/AI approaches, staying current with cutting-edge research and methodologies·       Developing ML solutions for AIOps and IT operations using large-scale operational data·       Collaborating with cross-functional teams: Working closely with product managers, and other stakeholders to ensure the AI/ML solutions align with the organization's goals and objectives·       Communicating effectively: Clearly document your work and effectively communicate your findings, insights, and recommendations to both technical and non-technical stakeholders, fostering a collaborative and informed environment.·       Guiding ML engineering decisions including model selection, feature engineering, and optimization strategies·       Working closely with AI Systems Tech Leads to ensure delivery of optimized AI systems and services to production You will be a great fit if you have: 
·       Relevant undergraduate degree in computer science, engineering, mathematics, or a similar discipline required. Advanced degree in AI/ML or a related field preferred·       4+ years in ML engineering with demonstrated advanced development or research capabilities (innovative projects, publications, theses)·       Deep understanding of statistical modeling, time-series, and ML fundamentals; deep learning a plus·       Strong Python skills with ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face)·       Experience with unsupervised learning and clustering, including on unstructured text data·       Experience with anomaly detection  and time-series forecasting (Prophet, VAR, deep learning approaches)·       Working knowledge of causal inference and root cause analysis methods·       Ability to translate research papers into working implementations·       Solid foundation in software development practices (testing, version control, code review)·       Experience building and operating production ML services (APIs, streaming data, SQL, containers, cloud)·       Background in NLP is essential  ·       Experience with ML experiment tracking, model versioning, and reproducible research practices·       Track record of research publications or open-source ML contributions preferred·       Domain experience in AIOps, observability or ITSM preferred You excel in these key competencies: 
·       Collaborative Communication – Ability to work effectively with product managers, data scientists, and cross-functional engineering teams to deliver high-value solutions·       Analytical Problem Solving – Strong critical thinking and troubleshooting skills to diagnose complex production issues and develop effective, scalable solutions·       Ownership & Accountability – Demonstrates end-to-end responsibility for system reliability, performance, and operational excellence, including proactive monitoring and issue resolution·       Technical Leadership & Mentorship – Ability to guide, mentor, and elevate other engineers while fostering best practices in system design, code quality, and AI-assisted development·       Continuous Improvement Mindset – Proactively identifies technical debt, improvement opportunities, and innovative solutions to enhance system scalability, performance, and engineering practices