Experience 5 to 10 years About the Role We are looking for an experienced Data Scientist to join our team and help build the next generation of datadriven 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 largescale data engineering You will have the opportunity to take ownership of complex analytical problems develop productiongrade 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 Who You Are You are a handson 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 operationalise a solution You enjoy understanding the business problem behind the model and are able to communicate technical findings clearly to both technical and nontechnical stakeholder s 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 What Youll Do As a Data Scientist you will Design develop and productionise machine learning and statistical models Work with largescale 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 treebased models gradient boosting ensemble modelling clustering ranking and deep learning where appropriate Develop endtoend 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 realtime prediction pipelines Build reusable analytical frameworks rather than oneoff solutions Design automated dataquality and modelquality checks Investigate production issues and perform rootcause 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 objectives Present model results insights recommendations and tradeoffs to business stakeholders and leadership Technology Youll Work With Our environment includes modern cloud data and machine learning technologies You may work with Data Cloud Platforms SnowflakeDatabricksAWSMicrosoft AzureGoogle Cloud PlatformProgramming Data PythonSQLPySparkPandasNumPyMachine Learning ScikitlearnXGBoostLightGBMCatBoostMLflowSHAPTensorFlow PyTorchEngineering MLOps GitDockerKubernetesREST APIsFastAPICI CDModel registriesAutomated ML pipelinesCloudbased model deployment and monitoringYou do not need experience with every technology listed above We value strong fundamentals and the ability to learn new technologies quickly What Were Looking For Required Bachelors or masters degree in data science Computer Science Statistics Mathematics Engineering Economics or another quantitative discipline Strong skilled experience in Data Science Machine Learning Advanced Analytics or a related field Strong proficiency in Python and SQL Strong understanding of machine learning and statistical modelling Experience developing predictive models using realworld datasets Experience with feature engineering model evaluation and model optimisation Experience working with large and complex datasets Strong understanding of model validation and performance metrics Ability to translate business requirements into analytical and machine learning solutions Strong problemsolving and analytical skills Ability to communicate complex technical concepts to different audiences What Youll Get This role provides the opportunity

📌 Data Scientist Mortgage Analytics and AI (Chennai)
🏢 loanDNA
📍 Chennai