Data Scientist - Financial Modelling & AWS (Bengaluru)

\/p> Data Scientist - Financial Modeling & AWS<\/span><\/b> <\/div> <\/span> <\/p> - Location: <\/span><\/b>India (Gurgaon) / Bangalore - Two days per month WFO<\/span> <\/span><\/li> - Employment Type: 6 month Contract <\/span><\/b> <\/span><\/li> - Budget: INR 250k per month<\/span><\/b> <\/span><\/li> - Primary Focus :<\/span><\/b>Financial forecasting & risk modelling; AWS -based model development<\/span> <\/span><\/li> - Immediate Joiners only<\/span><\/span><\/b> <\/span><\/li> - Yrs. of Exp: 6 + <\/span><\/span><\/b><\/span> <\/li> - Location<\/b> - Permanent Remote with Mandatory 2 Days in a month from Gurgaon / Bengaluru office <\/span> <\/li><\/ul> Role Summary<\/span><\/span> <\/span><\/h1> We are seeking a hands -on Data Scientist with expertise in financial modelling and AWS -based solutions. You will design, develop, and deploy advanced statistical and machine learning models that turn complex financial data into actionable insights and scalable, production -ready solutions.<\/span> <\/p> Key Responsibilities<\/span><\/span> <\/span><\/h1> - <\/span><\/span><\/span><\/span>Build predictive and prescriptive models for financial forecasting, risk analysis, and decision optimization.<\/span> <\/span><\/li> - <\/span><\/span><\/span><\/span>Apply statistical and machine learning techniques to improve business outcomes and model performance.<\/span> <\/span><\/li> - <\/span><\/span><\/span><\/span>Perform data wrangling, cleansing, and feature engineering on large structured and unstructured datasets.<\/span> <\/span><\/li> - <\/span><\/span><\/span><\/span>Develop and maintain robust ETL pipelines for financial data; ensure reproducibility and data lineage.<\/span> <\/span><\/li> - <\/span><\/span><\/span><\/span>Use AWS services (e.g., SageMaker, Glue, Redshift, Lambda) for model development, training, and deployment.<\/span> <\/span><\/li> - <\/span><\/span><\/span><\/span>Design solutions that are secure, scalable, and cost -efficient on AWS.<\/span> <\/span><\/li> - <\/span><\/span><\/span><\/span>Partner with cross -functional stakeholders to align modeling approaches with business objectives.<\/span> <\/span><\/li> - <\/span><\/span><\/span><\/span>Present insights, model outcomes, and recommendations to technical and non -technical audiences clearly.<\/span> <\/span><\/li><\/ul> Required Skills & Qualifications<\/span> <\/h1> - <\/span><\/span><\/span><\/span>Strong programming skills in Python, PySpark, and SQL.<\/span> <\/span><\/li> - <\/span><\/span><\/span><\/span>Hands -on experience with AWS services for data science workflows (e.g., SageMaker, Glue, Redshift, Lambda).<\/span> <\/span><\/li> - <\/span><\/span><\/span><\/span>Solid understanding of financial principles and quantitative analysis.<\/span> <\/span><\/li> - <\/span><\/span><\/span><\/span>Proven ability to deliver end -to -end data science projects in production environments.<\/span> <\/span><\/li> - <\/span><\/span><\/span><\/span>Solid problem -solving skills and ability to translate ambiguous requirements into measurable outcomes.<\/span><\/span> <\/li><\/ul> Preferred Qualifications<\/b><\/span><\/span> <\/span><\/span><\/div> - <\/span><\/span><\/span><\/span>Familiarity with big data technologies (Hadoop, Spark).<\/span> <\/span><\/li> - <\/span><\/span><\/span><\/span>Knowledge of data visualization / BI tools (e.g., Tableau, Power BI).<\/span> <\/span><\/li> - <\/span><\/span><\/span><\/span>Experience with MLOps and model monitoring in production environments.<\/span> <\/span><\/li><\/ul> <\/div><\/span> .