Summer Intern, Machine Learning

As a leading financial services and healthcare technology company based on revenue, SS&C is headquartered in Windsor, Connecticut, and has 27,000+ employees in 35 countries. Some 20,000 financial services and healthcare organizations, from the world's largest companies to small and mid-market firms, rely on SS&C for expertise, scale, and technology.

Job Description

Job Title: Summer Intern, Machine Learning

Location: London

Get To Know The Team:

We are looking for a motivated intern interested in applying machine learning to solve challenges in our Fund Services business.  We are interested in candidates that are comfortable building software systems using Python to develop and deploy machine learning pipelines.  Experience with Linux and using Docker would be advantageous.

The successful candidate will work within our Fund Services business working on a specific research project with the aim of producing a software solution that can be deployed and used.  The role is based in our London office with the opportunity for collaboration with a global team.  Candidates are expected to have communication skills to meet the challenges of this working environment.

Why You Will Love It Here!

• Opportunity: Work with a team applying leading edge technologies to business problems
• Flexibility: Business casual dress code
• Wide Ranging Perspectives: Collaborate with our global team with a variety of backgrounds, talents and experience
• Training: Hands-On, Team-Customized, including SS&C University

What You Will Get To Do

• Work on a specific research project
• Produce a working software solution that can be deployed and used
• Participate in the regular meetings of the team for a broader perspective
• Present your findings and solution to the global team

What You Will Bring

• Studying for or completed a Bachelor’s Degree or similar in Mathematics, Physics, Computer Science, or a related field
• Experience using Python for systems development
• Strong knowledge of statistics, probability and machine learning
• Supervised and unsupervised machine learning approaches
• Statistical techniques such as regression, clustering and dimensionality reduction
• Strong knowledge of neural networks and stochastic gradient descent
• Ability to work in a distributed team
• Drive and passion to gain new skills

Other desirable skills include Docker, SQL, Angular, GitHub version control and experience with a CI/CD tool such as GitHub Workflows.

SS&C is a global provider of services and software for the financial services and healthcare industries. Founded in 1986, SS&C is headquartered in Windsor, Connecticut, and has offices around the world. Some 18,000 financial services and healthcare organizations, from the world's largest companies to small and mid-market firms, rely on SS&C for expertise, scale and technology.

SS&C is leading the way.  We continue to look for todays and tomorrow’s brightest talent, those that embody a spirit to improve not only their lives, but those around them. From college students to seasoned and experienced professionals, we encourage you to apply. SS&C prides itself on hiring diverse, honest, dynamic individuals, who value collaboration, accountability, and innovation to name a few. 

We encourage applications from people of all backgrounds to enable us to bring diverse perspectives to our thinking and conversation. It's important to us that we strive to have a workforce that is diverse in the widest sense.

Thank you for your interest in SS&C! If applicable, to further explore this opportunity, please apply directly with us through our Careers page on our corporate website @ 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 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.