Job Description - Collect, clean, transform, and analyze large datasets for machine learning projects.
- Develop and maintain data-processing scripts and automated data pipelines.
- Prepare structured and unstructured data for machine learning models.
- Design, develop, validate, deploy, and maintain predictive machine learning models. Develop models for propensity scoring, account prioritization, segmentation, next-best-action and treatment optimization.
- Establish model benchmarks and perform back-testing against existing scoring methods and actual business outcomes. Monitor model performance and implement appropriate retraining, versioning and continuous-improvement processes as new outcome data becomes available.
- Develop feature engineering strategies using structured and unstructured enterprise data, potentially including account characteristics, transaction and payment history, digital engagement, communication outcomes, call transcripts and third-party data.
- Perform data validation, quality checks, and troubleshooting.
- Integrate model scores and recommendations into operational systems and workflows through Snowflake, APIs, BI platforms and other applications.
- Partner with business leaders and domain experts to translate operational problems into measurable machine learning use cases, target variables and model objectives.
- Develop methods for measuring the financial and operational impact of deployed models, including lift and ROI.
- Communicate model methodology, performance, limitations and business implications to both technical and nontechnical stakeholders. Skills and Requirements - Bachelor's degree in Computer Science, Data Science, Information Technology, Mathematics, Statistics, Engineering, or a related field.



Advanced degree preferred but not required with appropriate experience.
- Experience with Python and SQL.
- Demonstrated experience developing, validating and deploying machine learning models in a production business environment.
- Knowledge of data structures, algorithms, and software development practices.
- Familiarity with libraries such as Pandas, NumPy, and Scikit-learn.
- Experience with supervised learning, classification, ranking/scoring models, feature engineering and statistical model evaluation.
- Experience with Snowflake or comparable up-to-date cloud data platforms.
- Understanding of model lifecycle management, including testing, deployment, monitoring, retraining and version control.
- Strong analytical and problem-solving skills.
- Ability to work effectively with data scientists, engineers, and business teams.
- Ability to translate business objectives into measurable predictive-modeling problems and explain technical results to executive and operational stakeholders.
-
- Experience with TensorFlow or PyTorch..
- Experience with Spark, Databricks, Airflow, or similar data technologies.
- Knowledge of APIs and data integration.
- Familiarity with Git and CI/CD practices.
- Experience with NLP, generative AI, or other ML applications.
- Experience with Snowflake ML, Snowpark, Cortex or related Snowflake data/AI capabilities.
- Experience in accounts receivable management,



collections, consumer or commercial credit, lending, debt purchasing, financial services or similar environments.
- Experience developing propensity-to-pay, default-risk, collectibility, segmentation, account-prioritization, treatment or next-best-action models.
- Experience incorporating customer/contact behavior, payment history, digital engagement or communication data into predictive models.
- Experience applying NLP or machine learning to call transcripts, speech analytics or other unstructured customer-interaction data.
- Experience with workforce analytics, including hiring/selection, employee performance, retention/turnover or workforce optimization.
- Experience applying predictive analytics across additional business functions such as client analytics, sales, revenue forecasting or operational optimization We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal employment opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment without regard to race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request to [email protected].

📌 AI/ML Engineer (Hyderabad)
🏢 Insight Global
📍 Hyderabad