AI​/ML NLP Research Scientist

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.

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

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/Tensor Flow, 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

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

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

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