Data Scientist

Data Scientist

Consolidated Analytics, Inc. Chennai, Tennessee, United States

At loanDNA , we believe great leadership starts with the right people. Our team is built on industry veterans and forward-thinkers who bring a powerful mix of mortgage expertise, technical skills, and a passion for innovation.

We hire leaders who understand the complexities of the mortgage and financial services industry and embrace emerging technologies—AI, automation, and advanced analytics—to deliver smarter, faster solutions for our clients.

From evaluating loan quality and collateral to shaping disposition strategies and optimizing performance, our leadership team combines hands-on experience with cutting-edge insight. Their perspective spans the full mortgage lifecycle, ensuring clients benefit from strategies that are both practical today and built for tomorrow.

We are looking for an experienced Data Scientist to join our team and help build the next generation of data-driven solutions for the mortgage and real estate industry.

In this role, you will work at the intersection of data science, machine learning, cloud technology, and large-scale data engineering
. You will have the opportunity to take ownership of complex analytical problems, develop production-grade machine learning solutions, and work with large volumes of mortgage, property, valuation, market, and transactional data.

You will work closely with Data Engineering, Product, Technology, Analytics, and Business teams to turn complex business problems into scalable data science solutions.

Mortgage domain experience is preferred but not required
. We are equally interested in candidates with strong data science fundamentals who are excited to learn the mortgage and real estate domain.

You are a hands-on Data Scientist who enjoys solving complex problems with data.

You are comfortable working across the complete machine learning lifecycle — from understanding raw data and identifying patterns to feature engineering, model development, validation, deployment, and production monitoring.

You are someone who can move between experimentation and production. You are equally comfortable writing Python to build a model, SQL to analyse hundreds of millions of records, and collaborating with engineers to ope rationalise a solution.

You enjoy understanding the business problem behind the model and are able to communicate technical findings clearly to both technical and non-technical stakeholders.

Most importantly, you are curious, analytical, and comfortable working in an environment where you are expected to explore, experiment, challenge assumptions, and continuously improve existing solutions.

• Design, develop, and product ionise machine learning and statistical models.
• Work with large-scale structured and unstructured datasets.
• Perform exploratory data analysis to identify patterns, trends, anomalies, and opportunities.
• Develop advanced feature engineering and data transformation pipelines.
• Build predictive models using techniques such as regression, tree-based models, gradient boosting, ensemble modelling, clustering, ranking, and deep learning where appropriate.
• Develop end-to-end ML pipelines covering data preparation, training, validation, deployment, scoring, and monitoring.
• Conduct model backtesting, benchmarking, hyperparameter optimisation, and performance analysis.
• Develop model explainability and interpretability using techniques such as SHAP and feature importance.
• Monitor model performance, data drift, feature drift, stability, coverage, and production accuracy.
• Develop scalable batch and real-time prediction pipelines.
• Build reusable analytical frameworks rather than one-off solutions.
• Design automated data-quality and model-quality checks.
• Investigate production issues and perform root-cause analysis.
• Identify opportunities to improve existing models, data pipelines, and analytical methodologies.
• Work closely with Data Engineers and Software Engineers to move models from experimentation into production.
• Translate business problems into measurable data science…