Manager, Data Scientist and Machine Learning Engineer Ocwen Financial Solutions Pvt. Ltd. - APAC

1.0 - 5.0 years

0 Lacs

karnataka

On-site

As a Data Scientist at our company, you will play a crucial role in supporting the development and deployment of machine learning models and analytics solutions that enhance decision-making processes throughout the mortgage lifecycle, spanning from acquisition to servicing. Your responsibilities will involve building predictive models, customer segmentation tools, and automation workflows to drive operational efficiency and improve customer outcomes. Collaborating closely with senior data scientists and cross-functional teams, you will be tasked with translating business requirements into well-defined modeling tasks, with opportunities to leverage natural language processing (NLP), statistical modeling, and experimentation frameworks within a regulated financial setting. You will report to a senior leader in Data Science. Your key responsibilities will include: - Developing and maintaining machine learning models and statistical tools for various use cases such as risk scoring, churn prediction, segmentation, and document classification. - Working collaboratively with Product, Engineering, and Analytics teams to identify data-driven opportunities and support automation initiatives. - Translating business inquiries into modeling tasks, contributing to experimental design, and defining success metrics. - Assisting in the creation and upkeep of data pipelines and model deployment workflows in collaboration with data engineering. - Applying techniques such as supervised learning, clustering, and basic NLP to structured and semi-structured mortgage data. - Supporting model monitoring, performance tracking, and documentation to ensure compliance and audit readiness. - Contributing to internal best practices, engaging in peer reviews, and participating in knowledge-sharing sessions. - Staying updated with advancements in machine learning and analytics pertinent to the mortgage and financial services sector. 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), preferably in mortgage, fintech, or financial services. - Required certifications: None Specific skills or abilities needed: - Experience working with structured and semi-structured data; exposure to NLP or document classification is advantageous. - Understanding of the model development lifecycle, encompassing training, validation, and deployment. - Familiarity with data privacy and compliance considerations (e.g., ECOA, CCPA, GDPR) is desirable. - Strong communication skills and the ability to present findings to both technical and non-technical audiences. - Proficiency in Python (e.g., scikit-learn, pandas), SQL, and familiarity with ML frameworks like TensorFlow or PyTorch.,

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