Quantitative Research and Investment in Art (YC W17)
Data Engineer
$100k – $120k • 0.25% – 1.0%
Our data engineers build tools and infrastructure to gather, prepare, analyze, and visualize art auction data. They work closely with data scientists and software engineers to productionize models, and with art experts to incorporate domain knowledge.
The data is composed of numerical, categorical, image, text, and temporal variables stored primarily in Postgres and analyzed in Docker images on a Kubernetes cluster on Google Cloud. We use the Python data science and machine learning stack: Python 3, jupyter, pandas, numpy, scikit-learn, seaborn, PyTorch, TensorFlow, NLTK, gensim, SpaCy, OpenCV, PIL, and others.
Responsibilities
We’re looking for a Data Engineer to:
- Work with our software engineers to refine the data pipeline and productionize models
- Interface with the operations team to incorporate art domain expertise into our models
- Perform analysis and investigations of our data to better understand what drives art prices
- Build out infrastructure, testing, model validation, and data visualization systems
- Incorporate knowledge and algorithms from many different domains
Qualifications
Candidates ideally have most of the following:
- BS/MS in Computer Science, Data Science, Engineering or some equivalent
- 2-3 post-undergraduate years of work experience, preferably startup experience
- Software architecture experience
- Experience working with Data Science Python libraries
- Experience developing production-grade ETL pipelines
- Experience working in professional environments
- Intrinsic motivation and the ability to learn quickly
- Strong communication skills and ability to work with a team
- Experience working at a start-up is a plus
- Art knowledge or industry experience is a plus
- Business/finance knowledge is a plus
Note:
This is not an entry-level position. Please do not apply if you do not have a few years experience working as an engineer. **No recent bootcamp grads.**
Benefits
- Unlimited Vacation
- 401K
- Health Insurance
- Snacks and team bonding events
- Flexible scheduling and option for remote work if needed
Location
All positions are competitively compensated and based in SoHo, NYC.
The data is composed of numerical, categorical, image, text, and temporal variables stored primarily in Postgres and analyzed in Docker images on a Kubernetes cluster on Google Cloud. We use the Python data science and machine learning stack: Python 3, jupyter, pandas, numpy, scikit-learn, seaborn, PyTorch, TensorFlow, NLTK, gensim, SpaCy, OpenCV, PIL, and others.
Responsibilities
We’re looking for a Data Engineer to:
- Work with our software engineers to refine the data pipeline and productionize models
- Interface with the operations team to incorporate art domain expertise into our models
- Perform analysis and investigations of our data to better understand what drives art prices
- Build out infrastructure, testing, model validation, and data visualization systems
- Incorporate knowledge and algorithms from many different domains
Qualifications
Candidates ideally have most of the following:
- BS/MS in Computer Science, Data Science, Engineering or some equivalent
- 2-3 post-undergraduate years of work experience, preferably startup experience
- Software architecture experience
- Experience working with Data Science Python libraries
- Experience developing production-grade ETL pipelines
- Experience working in professional environments
- Intrinsic motivation and the ability to learn quickly
- Strong communication skills and ability to work with a team
- Experience working at a start-up is a plus
- Art knowledge or industry experience is a plus
- Business/finance knowledge is a plus
Note:
This is not an entry-level position. Please do not apply if you do not have a few years experience working as an engineer. **No recent bootcamp grads.**
Benefits
- Unlimited Vacation
- 401K
- Health Insurance
- Snacks and team bonding events
- Flexible scheduling and option for remote work if needed
Location
All positions are competitively compensated and based in SoHo, NYC.
New York City
