• Responsible for design and development of production-grade Machine Learning ops and Gen AI solutions • Lead hands-on delivery of scalable GenAI solutions from problem framing → prototyping → evaluation → production → monitoring. • Build internal copilots/assistants (knowledge search, code/content generation) and client-facing products (conversational analytics, summarization, recommendations, workflow automation). • Design RAG pipelines, embedding strategies, vector search, and model orchestration; evaluate fine-tuning vs. prompt engineering. • Implement guardrails, safety filters, prompt/version management, latency/throughput optimizations, and cost controls. • Identify areas that require improvements or additional functionalities and use your expertise in machine learning and software engineering to architect and develop solutions that fill gaps in our ML platform and development ecosystem. • Analyze system performance, scalability, and reliability to pinpoint opportunities for enhancement. • Optimize the scalability, performance, and reliability of AI Team solutions by implementing best practices and leveraging industry-standard technologies. • Collaborate with infrastructure teams to ensure smooth integration and deployment of ML solutions. • Streamline data ingestion, preprocessing, feature engineering, and model training workflows to improve efficiency and reduce latency. • Evaluate and optimize model prototypes for real-world performance and integrate ML models into production systems with partner teams to communicate and understand technical requirements and challenges.

Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. We are seeking a Senior / Lead Data Scientist with strong expertise in forecasting, tree-based models, and large-scale data processing. The role requires hands-on experience with PySpark, Databricks, and Azure and the ability to lead end-to-end model development and deployment. Experience with MLOps / DevOps is a strong plus. Key Responsibilities - Collaborate with business partners to develop innovative solutions to meet objectives utilizing cutting edge techniques and tools. - Apply advanced data science techniques to identify patterns, inefficiencies, and bottlenecks across logistics and operations. - Build scalable data pipelines and analytical models using PySpark for large-scale datasets. - Develop predictive and prescriptive models to support decision-making in areas such as demand forecasting, routing, and inventory management. - Collaborate with cross-functional teams including operations, product, and engineering to translate business challenges into analytical solutions. - Communicate insights and recommendations clearly to stakeholders through data storytelling, visualizations, and presentations. - Share your passion for Data Science with the broader enterprise community; identify and develop long-term processes, frameworks, tools, methods and standards. - Collaborate, coach, and learn with a growing team of experienced Data Scientists. - Stay connected with external sources of ideas through conferences and community engagements

• Define and execute a research roadmap focused on quantum algorithms and computational methods • Conduct cutting-edge research in quantum optimization and quantum machine learning • Collaborate with quantum hardware vendors to co-design algorithms for performance • Publish research findings in top-tier scientific journals and present at international conferences • Identify and evaluate business applications for quantum computing, translating research into commercial value

• Track database set-up, testing, maintenance and data entry • Communicate with clients, project teams and vendors on data management matters • Review study documents, design and develop project specific guidelines and instructions • Design eCRF, Data Management and Data Validation Plans and test EDC databases • Ensure data entry, follow-up and validation, including manual CRF review and SAE reconciliation • Code medical data • Track and report metrics leading to database lock • Coordinate the processing, dispatch and archiving of CRFs/queries • Maintain Clinical Data Management working files • Perform database QC checks, prepare and attend audits • Train site staff and project teams on CRF completion and data management topics