Consultant - Rna

WNS (Holdings) Limited (NYSE: WNS), is a leading Business Process Management (BPM) company. We combine our deep industry knowledge with technology and analytics expertise to co-create innovative, digital-led transformational solutions with clients across 10 industries. We enable businesses in Travel, Insurance, Banking and Financial Services, Manufacturing, Retail and Consumer Packaged Goods, Shipping and Logistics, Healthcare, and Utilities to re-imagine their digital future and transform their outcomes with operational excellence.We deliver an entire spectrum of BPM services in finance and accounting, procurement, customer interaction services and human resources leveraging collaborative models that are tailored to address the unique business challenges of each client. We co-create and execute the future vision of 400+ clients with the help of our 44,000+ employees. Our global footprint spans 16 countries with 61 delivery centers worldwide including in China, Costa Rica, India, the Philippines, Poland, Romania, South Africa, Spain, Sri Lanka, Turkey, United Kingdom and the United States.

Responsibilities:1. Collaborate with the Clients' Advanced Analytics team to identify, scope, and execute advanced analytics efforts that address business questions, solve business needs, and deliver tangible business value.2. Stay up-to-date with the latest AI, ML, mathematical, and informatics modeling methodologies, ensuring proficiency in applying new and diverse methods and justifying their selection.3. Develop proof-of-concepts (POCs) to build internal capabilities and standardize common modeling processes.4. Lead and manage a team of Advanced Analytics professionals, providing technical guidance, mentorship, and conducting performance evaluations.5. Collaborate with cross-functional teams, including data scientists, machine learning engineers, and software developers, to establish best practices and streamline ML model deployment processes.6. Develop and maintain robust MLOps pipelines for training, testing, and deploying machine learning models, ensuring scalability, reliability, and reproducibility.7. Implement and maintain monitoring and logging systems to track the performance and health of deployed models, facilitating timely troubleshooting and issue resolution.8. Work closely with data engineering teams to ensure the availability and quality of data required for model training and inference.9. Define and enforce security and compliance measures to safeguard sensitive data and ensure adherence to regulatory requirements in the life sciences/pharma domain.10. Collaborate with IT teams to manage infrastructure requirements, cloud resources, and containerization for MLOps workflows.11. Participate in strategic planning, providing insights and recommendations for enhancing the organization's data-driven initiatives.12. Proactively identify and resolve operational challenges related to MLOps, driving process improvements and automation wherever feasible.Additional Information:- Effective interpersonal communication skills for successful customer consultation.- Strong teamwork and leadership abilities.- Self-management skills with a focus on timely and accurate completion of competing deliverables.- Demonstrated dedication to making a positive impact and improving lives.- Enthusiasm for bringing analytics to life and applying it to real-world business scenarios.- Commitment to staying informed about statistical and scientific advances for maximizing impact.- An insatiable desire to learn, innovate, and embrace challenges for the benefit of patients.Eligibility Criteria:Required Experience:1. Proven experience (4-10 years) in Data Scientist, MLOps Engineer, Machine Learning Engineer, or related roles.2. Desired 2-4 years of relevant experience in the Healthcare/Life Sciences/Pharmaceutical domain.Technical Skills:1. Expertise with core data science languages, predominantly Python and PySpark, with additional knowledge of R and Scala being advantageous.2. Experience working with Snowflake and various database systems, including SQL and NoSQL.3. Expertise with MLOps tools and frameworks to deploy, monitor, and maintain ML/DL models in production environments.4. Hands-on experience with popular MLOps tools and frameworks, such as GIT, MLflow, Kubeflow, TensorFlow Extended (TFX), or similar.5. Solid understanding of cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).6. Proficiency in Machine Learning, Deep Learning, Statistics, Text-Mining/NLP, forecasting, and Optimization.Good to Have Skills:1. Exposure or knowledge in Dataiku DSS (Data Science Studio), DataBricks, or Alteryx.2. Experience in working with Tableau/Power BI/Qlik

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  B.Tech / Masters in a quantitative discipline (e.g., Applied Mathematics, Computer Science, Bioinformatics, Statistics; Ops Research, Econometrics).