Data Scientist

Posted 23 Hours Ago
New York, NY
Senior level
Fintech • Payments • Financial Services
The Role
As a Senior Data Scientist at Octaura, you will drive the product lifecycle from ideation to deployment, develop advanced machine learning models, build scalable cloud-based infrastructure, collaborate with teams to understand client needs, and communicate insights to stakeholders.
Summary Generated by Built In

It's time to transform markets

Existing workflows within syndicated loan and CLO markets are painful for clients: they are outdated, overcomplicated, and time-consuming. It’s time for a change. 

Octaura is reimagining the way these markets trade, with efficiency, transparency and simplicity at the heart of what we do. We bring trading capabilities, data and analytics together for the first time on a digitized platform–fundamentally transforming the markets and streamlining workflows like never before. 

At Octaura, everyone belongs

It’s essential that Octaurians are confident in knowing they have the space to use their voice and talents. The world is diverse and we actively want our team to reflect this. We’re a values-driven company and by engaging, solving and evolving together, we create a culture that is collaborative, transparent, impactful and innovative. And fun!  

 

The role in a nutshell 

As a Senior Data Scientist at Octaura, you'll be a key member of our Product team, playing a critical role in the development and growth of our Data and Analytics products. This is an early-stage opportunity to shape the future of our data science initiatives and make a significant contribution to the company's success.

What You'll Do

  • Drive the full product lifecycle: From ideation and market research to model development, deployment, and performance monitoring, you'll be involved in every stage of creating impactful data-driven solutions.
  • Develop advanced models: You'll leverage your expertise in machine learning and statistical modelling to extract valuable insights from large and complex datasets, building predictive models that fuel our product offerings.
  • Build scalable infrastructure: Design, implement, and maintain cloud-based infrastructure on AWS and/or Azure to support our data processing and model deployment needs.
  • Collaborate effectively: Work closely with the Go-to-Market team to understand client needs and market trends, and partner with the Technology team to build robust data pipelines.
  • Communicate insights: Clearly and effectively communicate your findings to stakeholders across the company, translating complex data into actionable insights

The Opportunity

  • Make a real impact: You'll have a direct and significant impact on the company's growth and success.
  • Early-stage opportunity: Shape the future of our data science products and be a part of building something truly innovative.
  • Collaborative environment: Work alongside a talented and passionate cross functional teams in a supportive and collaborative environment.
  • Growth potential: Ample opportunities for professional development and career advancement within a rapidly growing startup.

The Person

  • Advanced degree and experience: PhD (or MSc + 5 years of experience) in statistics, physics, mathematics, computer science, or a related field.
  • Strong programming skills: Proficiency in Python and experience with popular machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
  • Proven modelling experience: A track record of building and deploying predictive models using machine learning algorithms.
  • Data analysis expertise: Strong analytical skills with the ability to analyse and interpret complex datasets, identify patterns, and draw meaningful conclusions.
  • Excellent communication: Exceptional written and verbal communication skills with the ability to explain technical concepts to both technical and non-technical audiences.  
  • Cloud proficiency: Experience with cloud-based architectures (AWS and/or Azure) is highly preferred.
  • Fintech/Financial Services experience is a plus: Experience in the financial services industry, particularly within the fixed income market, is a valuable asset.

If you are passionate about data science in finance, have a strong background in technical majors, and are excited about building predictive models and cloud-based infrastructure using AWS and Azure, we want to hear from you. As a startup, we offer a dynamic and entrepreneurial work environment, where you will have the opportunity to take ownership of your work and make a real impact on our business.

 

The base pay range for this position in New York is $150,000 - $175,000 annually. Pay may vary depending on job-related knowledge, skills, and experience. Equity and year-end bonus may be provided as part of the compensation package, in addition to a full range of medical, financial, and other benefits, dependent on the position offered. Applicants should apply via Octaura's internal or external careers site.


Octaura Work Perks

At Octaura, our people are our most valuable asset, and we are pleased to offer the following benefits to all full-time employees: 

  • Competitive compensation and equity 
  • Flexible Paid Time Off
  • Competitive Parental Leave  
  • Daily breakfast, coffee and snacks in the office 
  • 90% company-paid healthcare 
  • Onsite gym & discounted membership 

We’re committed to equal opportunity employment 

Octaura is committed to a diverse and inclusive workplace. We are an equal opportunity employer and do not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. 

Top Skills

Python
The Company
New York, New York
60 Employees
On-site Workplace
Year Founded: 2022

What We Do

Octaura is an electronic trading solution created by the industry – for the industry. Backed by eight major US financial institutions, Octaura has reimagined the way the syndicated loan and the CLO markets trade. Efficiency, transparency and simplicity are at the heart of what we do.

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