About The Role

We are looking for an exceptional NLP Research Scientist to advance the state of financial intelligence through natural language processing. As an NLP Research Scientist at Shipra, you will develop cutting-edge models that transform unstructured financial data into actionable investment insights. Your research will directly impact how professional investors analyze markets, understand companies, and make data-driven decisions.

What You Will Do

Design and implement advanced NLP models for financial document analysis, earnings call transcription, and market sentiment extraction Develop domain-specific language models trained on financial data including SEC filings, earnings transcripts, and analyst reports Build real-time news sentiment analysis systems that identify market-moving information before it impacts prices Create named entity recognition systems for extracting financial relationships, company hierarchies, and supply chain connections Research and implement transformer architectures optimized for financial text understanding and generation Collaborate with product teams to integrate NLP capabilities into user-facing financial intelligence tools Publish research findings and contribute to the broader NLP and fintech research communities Mentor junior researchers and establish NLP research best practices across the organization

About You

PhD in Computer Science, NLP, Machine Learning, or related field with focus on natural language processing 3+ years of experience developing production NLP systems at scale Deep expertise in transformer architectures, attention mechanisms, and large language model fine-tuning Experience with financial text analysis, document classification, or domain-specific language modeling Proficiency in Python, PyTorch/TensorFlow, and distributed training frameworks Track record of publications in top-tier NLP conferences (ACL, EMNLP, NAACL, etc.) Strong understanding of financial markets, instruments, and terminology preferred Experience with MLOps, model deployment, and production monitoring systems

Nice to Have

Experience with financial data sources such as SEC filings, Bloomberg APIs, or market data feeds Background in computational linguistics or financial text mining research Familiarity with multimodal models combining text, numerical data, and time series information Knowledge of financial regulations and compliance requirements for ML systems Experience with real-time processing systems and low-latency model inference Contributions to open-source NLP libraries or financial ML frameworks Understanding of quantitative finance concepts and trading strategies

Benefits

Competitive salary with significant equity upside in a fast-growing fintech company Comprehensive health, dental, and vision coverage for you and your family Flexible remote work options with quarterly team gatherings in Toronto Annual research conference budget and support for publishing academic papers Access to high-performance computing resources and premium datasets Generous professional development stipend for courses and certifications Stock options with potential for substantial returns as we scale Collaborative research environment with world-class ML and finance experts Opportunity to shape the future of AI-driven financial intelligence