Job
Description
NLP & Data Engineer - Risk Insights & Monitoring Engagement Type: Contract Contract Duration: 6 Months Domain: Banking / Finance Number of Openings: 1 We are seeking a highly skilled and experienced NLP & Data Engineer to contribute to our Risk Insights & Monitoring platform within the Banking/Finance sector. The ideal candidate will have a strong background in designing, implementing, and deploying state-of-the-art NLP models, coupled with robust data engineering capabilities and a passion for building high-quality, scalable software solutions. You will play a crucial role in leveraging natural language processing to extract valuable insights from unstructured data. Key Responsibilities: NLP Model Development & Implementation: Design and implement cutting-edge NLP models for tasks such as text classification, semantic search, sentiment analysis, named entity recognition (NER), and summary generation. Conduct thorough data preprocessing and feature engineering to enhance model accuracy and performance. Stay abreast of the latest developments in NLP and Machine Learning, integrating advanced techniques into our solutions. (Plus) Prior experience in agentic AI, Large Language Models (LLMs), prompt engineering, and generative AI. Data Engineering & Backend Development: Implement and deliver high-quality software solutions/components for the Credit Risk monitoring platform. Develop backend services and microservices using Java Spring Boot, J2EE, and REST APIs , ensuring high SLA for data availability and data quality. Proficiency in programming languages such as Python and Java , with experience in frameworks like TensorFlow, PyTorch, or Keras. Experience with data handling and processing tools like Pandas, NumPy, and SQL . Knowledge of SQL and PL/SQL (Oracle) and UNIX , including writing queries, packages, working with joins, partitions, looking at execution plans, and tuning queries. Cloud & DevOps: Experience building cloud-ready and migrating applications using Azure , with a strong understanding of Azure Native Cloud services, software design, and enterprise integration patterns. Experience using DevOps toolsets like GitLab and Jenkins . Build observability into solutions, monitor production health, assist in resolving incidents, and remediate the root cause of risks and issues. Strong desire to work with baked-in quality disciplines such as TDD (Test-Driven Development), BDD (Behavior-Driven Development), test automation, and DevOps principles. Collaboration & Mentoring: Collaborate closely with data scientists, software engineers, and product managers to align NLP projects with business objectives. Mentor developers, review code, and ensure adherence to best practices and standards. Share knowledge and expertise with colleagues, contribute to hiring, and actively participate in our engineering culture and internal communities. Quality & Compliance: 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 solutions by applying digital principles and implementing both functional and non-functional requirements. Stakeholder Management: Understand, represent, and advocate for client needs. Take ownership of assigned tasks through to ultimate resolution. Ensure accuracy and timeliness of delivering solutions using the best IT standards and practices. Expertise & Qualifications: Total Years of Experience: 8 to 10 years. Relevant Years of Experience: 5 to 8 years. Education: Bachelor of Engineering or equivalent. Domain Specific Experience: Ideally 8-10 years of experience in NLP-based applications focused on the Banking/Finance sector. Preference for experience in financial data extraction and classification. Mandatory Skills: NLP, Python . Desired Skills: SQL, Azure . Analytical & Communication: Strong analytical and problem-solving skills with the ability to think critically and creatively. Excellent verbal and written communication skills, with the ability to explain complex concepts to non-technical stakeholders. Learning Agility: Interested in learning new technologies and practices, reusing strategic platforms and standards, evaluating options, and making decisions with long-term sustainability in mind. Agile Mindset: Passion for and experience with Agile working practices. Additional Information: Approx. Vendor Billing Rate: INR 16,000 per day. Background Check: As per client policy.
