SS&C is a global provider of investment and financial services and software for the financial services and healthcare industries. Named to Fortune 1000 list as top U.S. company based on revenue, SS&C is headquartered in Windsor, Connecticut and has 20,000+ employees in over 90 offices in 35 countries. Some 18,000 financial services and healthcare organizations, from the world's largest institutions to local firms, manage and account for their investments using SS&C's products and services.

Job Description

Senior Data Scientist

Location: Waltham, MA

Get To Know The Team:

Your deep experience with artificial intelligence, NLP, language models and advanced analytics is matched by a passion to build great products, lead innovation, be a mentor and guide to other Engineering team members. In the past you have been part of a startup or corporate innovation team working in fast-moving environments. You can point to numerous examples which have demonstrated your ability to creatively solve technical challenges.

What we are searching for:

As a Sr. Data Scientist, you will be working with the largest repository of corporate, board-level business information in the world. You will work with Product Managers, Business Analysts, Data Analysts, User Experience Designers, ML Engineers, and Senior Executives to gather requirements and apply data science methodologies to solve complex business problems.

You should have deep expertise in analyzing large, complex data sets from multiple domains, and then translating this analysis to models that can run at scale in a SaaS business. You will be a part of an established global team focused on Analytics, Search, and Artificial Intelligence with researchers in developers in Waltham, MA, Bucharest, Romania, and Hyderabad, India all focused on the development of solutions for Investment Bankers, Private Equity, and other industries.

Skills Required:

Advanced NLP Development: Design, develop, and optimize the Natural Language Processing (NLP) models using state-of-the-art techniques, with a focus on understanding complex language structures, semantics, and context.
Large Language Model (LLM) Expertise: Leverage your expertise in working with large language models. Stay up to date with the latest advancements in LLMs and implement strategies for fine-tuning, transfer learning, and adapting these models to specific domains.
Quantization and Model Optimization: Implement advanced quantization techniques to optimize deep learning models for efficient deployment on resource-constrained environments, ensuring minimal loss in performance while reducing memory and computational demands.
Natural Language Generation (NLG): Utilize your deep knowledge of NLG techniques to develop systems that can generate coherent and contextually relevant human-like text, catering to various applications such as content creation, conversational agents, and data summarization.
AI Model Deployment: Take charge of deploying AI models into production environments, collaborating closely with DevOps and software engineering teams to ensure seamless integration, scalability, and real-time performance of NLP models in various applications.
Deep Learning Research: Stay at the forefront of deep learning research and methodologies, applying innovative techniques to address challenges in NLP tasks, such as named entity recognition, sentiment analysis, language translation, and more.
PyTorch Champion: Serve as the PyTorch expert within the team, driving the development process using PyTorch's flexible framework for designing, training, and deploying complex neural network architectures.
Algorithmic Development: Research, experiment, and develop novel algorithms that push the boundaries of NLP tasks, incorporating techniques like attention mechanisms, transformer architectures, and reinforcement learning to achieve state-of-the-art results.
Collaborative Problem Solving: Collaborate with cross-functional teams including data scientists, machine learning engineers, and domain experts to identify business challenges and propose NLP-based solutions that have a tangible impact.

A Plus:

Innovative Model Architecture: Design novel NLP architectures that integrate cutting-edge techniques such as cross-modal attention, graph neural networks, and unsupervised pre-training to solve complex multimodal language understanding tasks.
NLG Elevation: Elevate NLG capabilities by developing advanced systems that not only generate human-like text but also adapt tone, style, and domain-specific nuances to produce contextually relevant and emotionally resonant narratives.
Transformer Customization: Customize transformer-based architectures to specific domains and tasks, leveraging techniques like knowledge distillation, architecture pruning, and dynamic attention mechanisms to enhance efficiency and performance.

Responsibilities & Opportunities of the Role:

Work with the AI team in building a world-class software, functioning as a thought leader in ensuring team development efforts resulting in successful delivery of AI systems.
Collaborate with cross functional agile teams of software engineers, data engineers, ML engineers, Product Managers and others in building new product features.
Manage and execute entire data projects from start to finish including cross-functional project management, data gathering and manipulation, analysis and modeling, and communication of insights and recommendations.
Demonstrate a high degree of originality and creativity when developing solutions to solve problems like entity recognition, document classification etc. utilizing methods such as statistical analysis, natural language understanding and optimization, and deep learning.
Work independently to manage multiple projects at once while ensuring deadlines are met and data output is accurate and appropriate for the business. Must also be able to deal with ambiguity and make independent decisions about what data and approach is best for the task at hand.
Think strategically about data as a core enterprise asset and assist in all phases of the advanced analytic development process.
The scope of work includes Forecast, Prediction Models, Outlier Reporting, Risk Analysis, Document classification, Data Extraction, Adhoc analysis.
Implementation of Supervised and Unsupervised model development techniques.

Experience:

A minimum of 2 years of developing and deploying AI/NLP/LLM models.
Please note that applications without this experience will not be considered. Some of this experience needs to be with NLP and deep learning technologies.
Masters or Ph.D. with experience in Machine Learning/Statistics/Data Science.
Experience with traditional as well as modern machine learning/statistical techniques, including NLP algorithms, LLMs, and quantization strategies.
Strong implementation experience with high-level languages, such as Python, R or similar scripting languages.
Familiarity with Linux/Unix/Shell environments.
Strong hands-on skills in sourcing, cleaning, manipulating and analyzing large volumes of data.
Strong written and oral communication skills.
Intense intellectual curiosity – strong desire to always be learning.
Analytical, creative, and innovative approach to solving open-ended problems.
Solid understanding of software engineering practices and version control systems.
Excellent problem-solving skills and a passion for staying updated with the latest advancements in the field.
Experience with product development is a plus.
Experience with Financial Services is desired but not required. Much of our data relates to Investment Banking and M&A.

Thank you for your interest in SS&C! To further explore this opportunity, please apply through our careers page on the corporate website at www.ssctech.com/careers.

Unless explicitly requested or approached by SS&C Technologies, Inc. or any of its affiliated companies, the company will not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. SS&C offers excellent benefits including health, dental, 401k plan, tuition and professional development reimbursement plan. SS&C Technologies is an Equal Employment Opportunity employer and does not discriminate against any applicant for employment or employee on the basis of race, color, religious creed, gender, age, marital status, sexual orientation, national origin, disability, veteran status or any other classification protected by applicable discrimination laws.

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