Data Scientist

About us @Symphony

We’ve spent the last 10 years building a communication and markets technology company, powered by interconnected platforms: messaging, voice, directory and analytics. Over 1000 institutions use our modular technology built for global finance. Security is in our DNA with uncompromising data protection, end-to-end encryption and resilient architecture, all created on a foundation of trust with our customers . 

But that was only chapter one.We’re now building on our purpose-built network, expanding AI-powered, real-time collaboration, redefining flexibility with fully cloud-native software with our trader voice product, and rethinking the industry’s approach to identity verification, connection and intelligence. .

The opportunity and our ambition are huge. But we need passionate, dedicated individuals to get there. At Symphony we work hard and fast. Our unique blend of technology and financial services makes it an environment you won't get elsewhere.

Role Description:

The Analytics division of Symphony Communications is looking to fill an immediate opening for a highly skilled and motivated Junior Data Scientist / Data Scientist to join our team. As a Junior Data Scientist / Data Scientist, you will play a crucial role in developing and implementing cutting-edge AI and machine learning models to extract valuable insights from large datasets. You will collaborate with cross-functional teams to drive data-driven decision-making and contribute to the development of innovative solutions.

The position is part of the Solutions Center team, which is under the Market Solution Services umbrella. The position will report directly to the New York City-based Solutions Center Manager. Tasks may be supervised by other members of the Solutions Center team. 

Key Responsibilities 

Data Processing:Analyze large, complex datasets to identify trends, patterns, and insights relevant to financial markets, customer behavior, and business performance.

Pre-process and clean large datasets to extract relevant features for modeling, with an emphasis on Gen AI data preprocessing techniques.
Collaborate with data engineers and data scientists to ensure data quality and optimize data pipelines for Predictive analytics and Gen AI applications.Modeling and Evaluation:Utilize advanced statistical and machine learning techniques, including Gen AI technologies, to analyze and interpret complex datasets.
Evaluate model performance and iterate on models to improve accuracy and efficiency, especially in the context of Gen AI technologies.
Become a user of Symphony’s proprietary NLP software.Collaboration and Communication:Work closely with cross-functional teams, including software engineers, data engineers, and domain experts, to integrate AI models, particularly Gen AI models, into applications and systems.
Communicate complex technical concepts and findings to non-technical stakeholders in a clear and understandable manner.Continuous Learning:Stay abreast of the latest advancements in data science, machine learning, AI and financial technologies to bring innovative solutions to the organization.
Contribute to the organization's innovation by exploring and implementing new Gen AI techniques and methodologies.Periodic availability during US EST hours for team meetings.

Required Qualifications

Undergraduate degree, preferably in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.

Proficiency in Python, including hands-on experience with machine learning libraries and frameworks (e.g., Pandas, Pytorch, Tensorflow, HuggingFace).
Demonstrated experience in data science and machine learning through projects, internships, or prior roles, with exposure to or hands on experience with Gen AI concepts and technologies.
Familiarity with Cloud Computing Platforms (e.g., GCP, AWS).
Basic understanding of MLOps lifecycle (e.g., Git, Docker, CI/CD).
Flexibility to adapt to the changing demands of a fast-paced environment.
Willingness to learn domain knowledge in financial services, insurance, and other verticals represented by our client base.
Excellent Data Storytelling and Communication Skills.
Commitment to continuous improvement, with a passion for building processes/tools to improve efficiency.

Preferred Qualifications

Master's Degree in a related quantitative field.

Experience applying software engineering best practices in Python, such as object oriented programming (OOP) and Test-Driven Development (TDD).
Domain expertise in Finance, Banking and Financial Services, or Insurance.
Experience with prompt engineering, fine-tuning, and deploying LLMs.
Understanding of RESTful APIs and experience interacting with them; experience building web APIs is a plus.
Experience writing SQL queries (e.g., PostgreSQL, SQLite); familiarity with NoSQL databases (e.g., MongoDB) is a plus.

Compensation:

Competitive salary

Bonus Plan
Benefits and Perks vary based on location.

Benefits and Perks:

Regional specific competitive benefits

Build your own Benefits (BYOB) perk
Many other fun and exciting benefits and activities!