Lead Data Scientist- Collections Campaign Spocto

8.0 - 12.0 years

0 Lacs

chennai, tamil nadu

On-site

About the Role As a skilled Lead Data Scientist at Yubi, you will play a crucial role in designing, developing, and deploying ML/ RL models for Collection Campaign Recommendations/ Optimizations. Your primary responsibility will be to experiment and optimize collection campaigns across digital, telecalling, and field platforms. Leveraging your expertise in machine learning and strong Python programming skills, you will drive innovation and deliver business value for our clients. Key Responsibilities - Develop, implement, and maintain advanced analytical models and algorithms tailored to enhance debt collection processes. - Collaborate with business stakeholders to identify data-driven opportunities for improving debt collection strategies. - Continuously enhance existing models and integrate new data sources to optimize our approach. - Take ownership of the end-to-end process of metric design, tracking, and reporting related to debt collection performance. - Regularly improve and update metrics to align with business objectives and regulatory requirements. - Effectively communicate findings to both technical and non-technical stakeholders. - Mentor, train, and support junior data scientists, fostering a culture of continuous improvement and collaboration. - Lead cross-functional teams on data projects, ensuring alignment between data science initiatives and business goals. - Stay updated on the latest industry trends, tools, and best practices in analytics and debt management. Required Skills Technical Skills: - Profound understanding of machine learning algorithms, including supervised, unsupervised, and ensemble methods, and their application to risk. - Expertise in statistical analysis, hypothesis testing, regression analysis, probability theory, and data modeling techniques to extract insights and validate machine learning models. - Experience in designing, developing, and delivering end-to-end data products and solutions. - Proficiency in model explainability techniques (e.g., SHAP, LIME) and regulatory compliance for risk models. - Strong proficiency in Python. - Familiarity with PySpark is a plus. - Ability to build and deploy models on cloud platforms (AWS). - Proficiency in developing backend microservices using Fast API and working knowledge of MLOps. - Good to have experience with NLP techniques. Domain Skills (Good to have): - Previous domain expertise in debt collection processes, credit risk assessment, regulatory compliance, and industry best practices. - Demonstrated ability to design, implement, and optimize performance metrics and key performance indicators tailored for debt recovery initiatives. Education and Experience: - Bachelor's/Advanced degree in Data Science, Statistics, Mathematics, Computer Science, or a related field. - 5 to 8 years of experience in the data science and machine learning domain. - Experience in the financial sector or Collection team is a bonus.,

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AI Lead - VP - 10th May -F2F interview Deutsche Bank

14 - 24 years

30 - 45 Lacs

Pune

Hybrid

Role & responsibilities Please Note - This is not a walk in interview only shortlisted candidates will be called. Your key responsibilities Proven ability to design, build, and deploy end-to-end AI/ML systems in production. Expertise in data science , including statistical analysis, experimentation, and data storytelling. Experienced in working with large-scale, real-world datasets for model training and analysis. Comfortable navigating urgency, ambiguity, and fast-changing priorities . Skilled at solving complex ML problems independently , from idea to implementation. Strong leadership experience building and guiding high-performing AI teams . Hands-on with deep learning, NLP, LLMs , and classical ML techniques. Fluent in model experimentation, tuning, optimisation , and evaluation at scale. Solid software engineering background and comfort working with data and full-stack teams . Experience with cloud platforms (GCP, AWS, Azure) and production-grade ML pipelines. Bias for action willing to jump into code, data, or ops to ship impactful AI products . Your skills and experience PhD in Computer Science, Data Science, Machine Learning, AI, or a related field. Strong programming skills in Python (preferred), with experience in Java, Scala, or Go a plus. Deep expertise with ML frameworks like TensorFlow, PyTorch, Scikit-learn. Experience with large-scale datasets , distributed data processing (e.g. Spark, Beam, Airflow). Solid foundation in data science : statistical modeling, A/B testing, time series, and experimentation. Proficient in NLP, deep learning , and working with transformer-based LLMs . Experience with MLOps practices — CI/CD, model serving, monitoring, and lifecycle management. Hands-on with cloud platforms (GCP, AWS, Azure) and tools like Vertex AI, SageMaker, or Databricks. Strong grasp of API design , system integration, and delivering AI features in full-stack products. Comfortable working with SQL/NoSQL , and data warehouses like BigQuery or Snowflake. Familiar with ethical AI, model explainability , and secure, privacy-aware AI development

Posted 2 months ago

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