Senior Staff Engineer, Data Science

📋 Description • Own the end-to-end data science lifecycle for Fortune-500 and high-growth clients, translating complex business problems into elegant, production-grade ML solutions that deliver measurable ROI. • Architect and implement cutting-edge generative-AI applications—leveraging RAG, text-to-SQL, and LLM fine-tuning—to unlock new revenue streams and automate high-value workflows. • Lead the design and deployment of scalable ML pipelines on AWS, Azure, or GCP, using Docker and Kubernetes to ensure reproducibility, security, and 99.9 % uptime in multi-region environments. • Establish rigorous experimentation frameworks for classification, regression, forecasting, anomaly detection, market-mix modeling, and recommendation systems, driving statistically significant improvements in KPIs. • Champion best-practice code craftsmanship: write, review, and merge Python/R modules that are clean, tested, and documented, while enforcing linting, type-hinting, and CI/CD standards across the team. • Translate ambiguous business requirements into crisp technical specifications, producing architecture blueprints, data-flow diagrams, and decision matrices that empower squads to deliver on time and on budget. • Conduct deep-dive root-cause analyses for model drift, data-quality issues, and latency bottlenecks; implement corrective actions that cut error rates by double-digit percentages. • Run rapid POCs to validate emerging techniques—such as graph neural networks, reinforcement learning, or transformer-based NLP—then socialize findings through internal tech talks and client workshops. • Mentor and level-up a distributed team of data scientists and ML engineers, pairing on complex problems, sharing curated learning paths, and fostering a flat culture where every voice is heard. • Travel up to once a month to client sites across North America, Europe, or APAC to whiteboard solutions, build trust with C-suite stakeholders, and ensure strategic alignment. • Define non-functional benchmarks (latency <100 ms, throughput >10 k TPS, cost <$0.001 per prediction) and bake them into the design phase, preventing surprises at go-live. • Collaborate with product managers, UX designers, and DevOps to embed ethical-AI guardrails, privacy controls, and explainability features that exceed regulatory standards. • Continuously scan the horizon for new tools—vector databases, feature stores, experiment-tracking platforms—and pilot the most promising to keep Nagarro at the forefront of innovation. • Contribute to pre-sales pursuits by crafting compelling solution proposals, effort estimates, and risk-mitigation plans that win multi-million-dollar engagements. • Publish thought-leadership blogs, speak at meetups, and file patents that amplify Nagarro’s brand as a global leader in data science and AI engineering. 🎯 Requirements • 10+ years of hands-on experience delivering data science and machine-learning solutions in enterprise environments. • Expert-level proficiency in Python or R for data science, plus deep knowledge of SQL, statistics, probability, and data visualization. • Proven track record with generative-AI fundamentals, RAG architectures, text-to-SQL, and LLM deployment. • Production experience deploying models via Docker and Kubernetes on at least one major cloud (AWS, Azure, or GCP). • Strong communication and stakeholder-management skills, with the ability to travel onsite once a month. 🏖️ Benefits • Fully remote-first culture with flexible hours and no micromanagement. • Dedicated annual training budget and paid certifications to keep your skills razor-sharp. • Opportunity to file patents and publish research under the Nagarro brand. • Global mobility program allowing short- or long-term assignments across 30+ countries.