Assistant Manager-Data Science

7 days ago


PunePimpriChinchwad Area, India WNS Full time ₹ 15,00,000 - ₹ 25,00,000 per year

Company Description
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.

Job Description
Job Summary:We are seeking a highly skilled and innovative Data Science Professional to join our analytics team part of the Automation Center of Excellence. The ideal candidate will have strong Python programming capabilities, hands-on experience with Microsoft Power Platform, familiarity with WTW Unify and a keen understanding of Generative AI (GenAI) technologies. Knowledge of Dataiku is a plus.This role involves developing data-driven solutions, automating workflows, and leveraging AI to drive business insights and operational efficiency.Job Description Roles and responsibilities The ideal candidate should have strong communication skills to effectively engage with both technical and non-technical stakeholdersThe candidate will be responsible for developing end to end task/workflow automation pipeline using Python using wide range of data sources (both on premise and cloud)Candidate should have strong working experience is transforming excel based manual processes to fully automated python based process incorporating strong governance around itThe person should be competent in Python Programming and possess high levels of analytical skills - Data pre-processing, engineering, data pipeline development and automation In-depth knowledge of libraries such as pandas, numpy, scikit-learn, openpyxl, pyxlsb, TensorFlow, PyTorch etc.Well-versed with Python coding standards and formatting conventions to ensure maintainable, scalable, and reusable modules.Build and automate workflows using Microsoft Power Platform (Power BI, Power Apps, Power Automate), having BI skills - Qlik Sense, Sigma Reporting tool will be a plusintegrating systems and automating workflows using WTW Unify Apply GenAI techniques to enhance data exploration, automate content generation, and support decision-making.Experience working on Posit Workbench, Posit Connect will be an added advantageEnsure data quality, governance, and compliance with organizational standards.Well-versed with CI/CD pipelines using Azure DevOps (ADO) for seamless deployment and integration of data science solutions.Stay updated with the latest trends in AI, machine learning, and data engineering.Knowledge of Dataiku is a plus.Tools/Tech experience – Mandatory – Python (Data processing, Engineering & Automation), SQL, Proficiency with version control systems like ADO/BitbucketPreferred - R programming, Posit Workbench, R Shiny Experience processing large amount of data using BigData technologies is preferredFamiliarity with Microsoft Power Platform tools.Familiarity with WTW Unify platform and its applications in analytics.Knowledge of Dataiku is a plus.Knowledge of Generative AI models and frameworks (e.g., GPT, DALL·E, Llama).Knowledge of data visualization tools and techniques is a plus - Power BI, Sigma, Qlik Sense, Tableau etcFunctional/Other expertiseRelevant experience: 5 – 7yrs years of experience using Python programming Language for end-to-end data pre-processing, transformation and automationExperience in the Insurance domain preferred (for e.g. Finance, Actuarial)

Qualifications
Masters in Statistics/Mathematics/Economics/Econometrics from Tier 1 institutions Or BE/B-Tech, MCA or MBA from Tier 1 institutions


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