Senior Manager, Data Science and Analytics at Onity

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

05 Jul, 26

Salary

0.0

Posted On

06 Apr, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, Machine Learning, Statistical Modeling, Data Science, Predictive Modeling, Natural Language Processing, Data Pipelines, Model Deployment, Risk Scoring, Churn Prediction, Segmentation, Document Classification, Scikit-learn, Pandas, TensorFlow

Industry

Financial Services

Description

Position Summary: We’re seeking a Data Scientist to support the development and deployment of machine learning models and analytics solutions that improve decision-making across the mortgage lifecycle—from acquisition to servicing. In this hands-on role, you’ll contribute to building predictive models, customer segmentation tools, and automation workflows that enhance operational efficiency and customer outcomes. You’ll work closely with senior data scientists and cross-functional teams to translate business needs into well-scoped modeling tasks, with opportunities to apply natural language processing (NLP), statistical modeling, and experimentation frameworks in a regulated financial environment. This role reports to a senior leader in Data Science. Job Functions and Responsibilities: * Develop and maintain machine learning models and statistical tools for use cases such as risk scoring, churn prediction, segmentation, and document classification. * Collaborate with Product, Engineering, and Analytics teams to identify data-driven opportunities and support automation initiatives. * Translate business questions into modeling tasks and contribute to the design of experiments and success metrics. * Assist in building and maintaining data pipelines and model deployment workflows in partnership with data engineering. * Apply techniques such as supervised learning, clustering, and basic NLP to structured and semi-structured mortgage data. * Support model monitoring, performance tracking, and documentation to ensure compliance and audit readiness. * Contribute to internal best practices and participate in peer reviews and knowledge-sharing sessions. * Stay current with developments in machine learning and analytics relevant to mortgage and financial services. Qualifications: * Minimum education required: Masters or PhD in engineering/math/statistics/economics, or a related field * Minimum years of experience required: 2 (or 1, post-PhD), ideally in mortgage, fintech, or financial services * Required certifications: None * Specific skill or ability needed * Experience working with structured and semi-structured data; exposure to NLP or document classification is a plus. * Understanding of model development lifecycle, including training, validation, and deployment. * Familiarity with data privacy and compliance considerations (e.g., ECOA, CCPA, GDPR) is preferred. * Strong communication skills and ability to present findings to technical and non-technical audiences. * Minimum software or applications experience required/preferred * Proficiency in Python (e.g., scikit-learn, pandas), SQL, and familiarity with ML frameworks like TensorFlow or PyTorch. * Minimum experience required using mobile technology: None * Any other requirements an ideal applicant needs to have that is not covered by above: None

Responsibilities

Develop and maintain machine learning models and statistical tools to support risk scoring, churn prediction, and automation workflows. Collaborate with cross-functional teams to translate business needs into modeling tasks and ensure compliance with financial regulations.