About us
RationalAi develops explainable "white box" solutions to manage financial and operational risks for our clients in financial services and industrial companies. We work with a firm’s leadership to facilitate decision-making process using analytics. We are based in the New York City area. We are a growing, revenue positive startup and looking for great people to share our journey.

Why work with us?

  1. You will solve real problems that have an enormous impact on the bottom line.

  2. You will learn a ton. Your colleagues are experts in statistics, machine learning, and business strategy.

  3. We treat each other respectfully and are committed to each other’s professional development.

What roles are we currently hiring for?
We are hiring for intern and full-time positions for data scientists, data engineers and software engineers. Descriptions for each role are below


What will you be doing?
Perform end-to-end data analysis. We try to align your duties with your interests. But, we are a small company and everyone is expected to pitch in as-needed. Sample projects are below:

  • Rapid failure detection. Using an anomaly detection scheme developed by us, we designed and implemented an efficient way to rapidly detect when any of 50,000+ machines in a network have failed.

    • Data: multiple TB of multivariate time-series data.

    • Analytics techniques: Censored regression

    • Compute: Dedicated 20-node cluster

  • Credit underwriting for non-traditional borrowers. We are developing analytics for credit products (credit cards, business loans, auto loans, ..) for individuals who are not covered by traditional creditworthiness metrics. This includes identifying and collecting alternative data, developing AI-based underwriting models and developing and deploying a digital ad campaign to market the products.

    • Data: Multiple data sources, some of them collected by us

    • Analytics techniques: Propensity matching, linear regression, gradient boosting, NLP, monotone random forests

    • Compute: AWS/Google cloud

Logistics

  • Timing: Start immediately or at a mutually convenient date.

  • Time commitment: Full-time. If you are only available part-time, you need to be available for at least 20 hours per week.

  • Paid and unpaid internships are offered.

  • We are hiring at different levels from interns to experienced professionals.

  • The positions are open to individuals with authorization to work in the US.

Data Scientist/Data Engineer Role

Must-have skills:

  • Strong Python coding for data pulling, data cleaning, exploratory data analysis, basic statistical analysis.

  • Ability to use the pandas package well.

  • Write clean code (well-commented, appropriate variable names, modular, unit tests, log files, sensible exception handling, PEP8 compliant, ...).

  • Good written and verbal communication skills in English.

  • Ability to work independently, take ownership of your work and get things done.

  • Willingness to roll up your sleeves and get whatever needs to get done to move a project forward. Sometimes this may mean learning and implementing a new algorithm. At other times it may mean doing un-glamorous stuff such as data cleaning, refactoring someone else’s code, or developing a simple BI tool to communicate your results.

  • Familiar with github

  • Only for Data Scientists: Solid working knowledge of Statistics 101. You should know how to perform univariate tests, linear regression, .. and understand when things can go wrong.

  • Only for Data Engineers: Solid working knowledge of SQL.

Great-to-have skills but not mandatory(You will need to acquire these skills shortly after joining)

  • Only for Data Scientists:

    • Working knowledge of how common machine learning algorithms actually work (ridge regression, xgboost, natural language processing)

    • Implement models using scikit-learn or other standard Python packages.

  • Only for Data Engineers:

    • Stand up and manage storage, compute and database solutions available on AWS, Google Cloud and other cloud providers.

How do I send in an application?
Please email: info@rationalai.co. Send in a strong, complete application. We are fortunate to be a great place to work and receive lots of applications. Incomplete applications are unlikely to receive further consideration.

What to include in the application:

1. Sample Python code

  • This is the most important part of your application. Please read through this section carefully.

  • Please provide a high quality sample. Some Python resources we found useful are here. We are looking for code that:

    • generally follows Python's PEP8 guidelines.

    • is modular

    • is relatively easy to debug when something goes wrong

    • is well--documented

  • You can include code examples from one project or across multiple projects. Please CLEARLY describe what each piece of code is meant to illustrate (e.g., "This file shows how I cleaned up raw data to handle missing values and other data problems", "This file shows how I evaluated the goodness-of-fit of the model", ...).

  • Please DON'T include examples that use the Titanic, Iris or home price data sets.

  • Please DON'T include examples related to image recognition.

  • If you are using deep learning, please also include results using some other algorithm.

  • Please DON’T send us printouts of your entire sets.

  • Please DON'T send us any confidential material. 

  • Please send your Python code as PDF or HTML files. NO .py or .ipynb files.

  • Please limit your Python code sample to a maximum of 20 pages.

  • Please send your material as separate files. Don’t zip them.

2. For at least one of the functions used in your sample, please include unit tests. If possible, please use the pytest package.

3. Please include an example of exception handling (using try: .. except: ), either as part of your sample Python code or as a separate toy example. A toy example is fine.

4. Please include an example of how you would use Python’s logging capabilities to keep track of how your program is working using Python’s logging example. A toy example is fine.

5. Your resume.

6. List of statistics and programming /software/ computer science courses you have taken.

7. For how long have you been coding in Python and in other programming languages.

8. Your availability (i.e., Please clarify if you are available full time or part time. If part-time, please tell us total hours/week and the days and times you are available.)


Software Engineer Role

We are looking for software engineers to help us with full-stack development to productionize our analytics. Interested in working on a bunch of projects and learning a ton along the way? Comfortable with ambiguity and taking on a bunch of responsibility? If so, this role is a good fit for you.

To apply, send in your coding sample, your level of expertise and programming experience in different programming languages, and resume to: info@rationalai.co