New York /
Rivet is building the strategic toolkit for capital productivity. Finance is a critical part of every enterprise. It sits at the center of almost all decisions and data flows and is charged with identifying the levers to improve business performance, and leading and validating capital allocation decisions. CFOs act as consiglieres to Boards and executive teams and wield a level of influence and autonomy in organizations that is only rivaled by the CEO. Despite this, most finance teams can only access software and services that were designed to solve problems from decades ago. Rivet is changing this.
Our mission is to ensure the most productive use of capital by unleashing finance and giving them unparalleled predictive capabilities and market access. We will shift finance from reactive decision-making to predictive and prescriptive reasoning — from the “what” to the “why”, the “so-what”, and the “what-if?” — and bring the leading edge of machine learning to finance.
The Rivet team is led by Nikhil Bharadwaj, formerly the Chief Operating Officer of Bloomberg L.P's Data organization, and is backed by leading early-stage investors. We are incredibly optimistic about our vision for finance, but equally aware that we have to figure out many details to bring it to life. We care deeply about the problem and get unreasonably excited about the turpentine of finance. We lead with the underdog mentality––we’re ambitious and relentless, but we don’t think we’re individually exceptional. This keeps us on our toes, so we’re continually learning from our customers and challenging and growing with each other.
We’re experienced builders and we’re bringing together engineers, data scientists, product and design taste-makers, financiers, and others from a variety of backgrounds to experiment with new ideas and rethink old assumptions to create a new world for our customers. Come build with us!
About the role
As an early member of the engineering team at Rivet, you’ll help define and establish our foundational engineering practices, drive the technology roadmap, and be a leader on a team that will grow quickly. Your hands-on contributions will have a huge impact on the product and our customers. You’ll also have the opportunity to contribute meaningfully to many other areas of the business and you will shape our culture, values, and ways of working in foundational ways.
What will you be doing in the role?
You will bring data and machine learning to the forefront of product development and decision making, and build data and machine learning pipelines for our financial intelligence engine, product KPIs, and forecasting applications. You will drive projects from nascent-idea to customer launch. You will own all the engineering aspects of data science by developing systems to build, run, and monitor ML models in production systems. You’ll obsess about engineering quality and execution decisions to increase customer value at a high-velocity. You will be on the ground floor of Rivet’s engineering team and mentor and lead junior members as the team scales. You’ll also work closely with engineering and product leaders to set long-term strategy, and build and recruit engineering and machine learning teams.
What would make you a good fit?
- You’re both relentless and kind, and don’t see these as being mutually exclusive
- You have a self-directed learning style, an insatiable curiosity, and a hands-on execution mindset
- You have deep experience working with product and engineering teams to launch machine learning products that users love in new or rapidly evolving markets
- You’ve implemented and engineered features for ML models, and can experiment effectively to pick the right approach, interpret results, and iterate to a working model with a minimum number of cycles
- You’ve experimented broadly and can help continuously raise the bar on collaborating with data scientists, choose the right tools and packages for rapid prototyping, deploy models into production, etc.
- You have excellent writing and speaking skills with a specific knack for connecting technical choices to product opportunities
- 7+ years of experience in Python and proficiency with pandas and NumPy
- 3+ years of experience engineering features and developing ML models using frameworks like Tensorflow, PyTorch, Keras, or Scikit-Learn and visualization packages such as matplotlib, seaborn, or plotly
- Deep understanding of machine learning techniques such as gradient boosting, random forests, etc
- 3+ years of experience developing ML pipelines in Python dealing with data ingestion, data modeling, and data management
- Demonstrable experience deploying and monitoring ML models in production environments. You are deeply familiar with model lifecycle management
- You have deep experience with data structures and algorithms, and SQL and Postgres
What’ll make you stand out (but not required)
- Experience working with deep learning frameworks and neural network architectures
- Experience modeling and forecasting financial data or time-series data
- Experience working with open source projects and the AWS stack