NLP & Data Engineer - Risk Insights & Monitoring

8 - 10 years

10 - 15 Lacs

Posted:1 month ago| Platform: Naukri logo

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Job Description

Number of Openings* 1 ECMS ID Duration of contract* 6 months Total Yrs. of Experience* 8 to 10 Relevant Yrs. of experience* 5 to 8 Detailed JD *(Roles and Responsibilities) Design and implement state-of-the-art NLP models, including but not limited to text classification, semantic search, sentiment analysis, named entity recognition, and summary generation. conduct data preprocessing, and feature engineering to improve model accuracy and performance. Stay updated with the latest developments in NLP and ML, and integrate cutting-edge techniques into our solutions. collaborate with Cross-Functional Teams: Work closely with data scientists, software engineers, and product managers to align NLP projects with business objectives. deploy models into production environments and monitor their performance to ensure robustness and reliability. maintain comprehensive documentation of processes, models, and experiments, and report findings to stakeholders. implement and deliver high quality software solutions / components for the Credit Risk monitoring platform. leverage his/her expertise to mentor developers; review code and ensure adherence to standards. apply a broad range of software engineering practices, from analyzing user needs and developing new features to automated testing and deployment ensure the quality, security, reliability, and compliance of our solutions by applying our digital principles and implementing both functional and non-functional requirements build observability into our solutions, monitor production health, help to resolve incidents, and remediate the root cause of risks and issues understand, represent, and advocate for client needs share knowledge and expertise with colleagues , help with hiring, and contribute regularly to our engineering culture and internal communities. Expertise - Bachelor of Engineering or equivalent. Ideally 8-10Yrs years of experience in NLP based applications focused on Banking / Finance sector. Preference for experience in financial data extraction and classification. Interested in learning new technologies and practices, reuse strategic platforms and standards, evaluate options, and make decisions with long-term sustainability in mind. Proficiency in programming languages such as Python Java. Experience with frameworks like TensorFlow, PyTorch, or Keras. In-depth knowledge of NLP techniques and tools, including spaCy, NLTK, and Hugging Face. Experience with data handling and processing tools like Pandas, NumPy, and SQL. Prior experience in agentic AI, LLMs ,prompt engineering and generative AI is a plus. Backend development and microservices using Java Spring Boot, J2EE, REST for implementing projects with high SLA of data availability and data quality. Experience of building cloud ready and migrating applications using Azure and understanding of the Azure Native Cloud services, software design and enterprise integration patterns. Knowledge of SQL and PL/SQL (Oracle) and UNIX, writing queries, packages, working with joins, partitions, looking at execution plans, and tuning queries. A real passion for and experience of Agile working practices, with a strong desire to work with baked in quality subject areas such as TDD, BDD, test automation and DevOps principles Experience in Azure development including Databricks , Azure Services , ADLS etc. Experience using DevOps toolsets like GitLab, Jenkins Strong analytical and problem-solving skills with the ability to think critically and creatively. Communication: Excellent verbal and written communication skills, with the ability to explain complex concepts to non-technical stakeholders. Takes ownership of tasks assigned to ultimate resolution. Accuracy and timeliness of delivering solutions using the best IT standards and practices Mandatory skills* NLP, Python Desired skills* SQL, Azure Domain* Banking / Finance Approx. vendor billing rate* INR 16000/Day Precise Work Location* Kharadi, Pune Background check process to be followed: * As per client Mode of Interview: Telephonic/Face to Face/Microsoft teams* Telephonic / Microsoft teams Video

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