Quantitative Developer, Machine Learning
Quantitative Developer, Machine Learning Technical Qualifications
- Coding experience in at least one of the following: Python, Java, Scala, C/C++
- Compute/ML at scale and big data tools (Hadoop, Spark, Presto, Kafka, Dask, Ray)
- Experience in the NLP domain
- Experience solving machine learning problems (e.g. logistic regression, random forest, xgboost, neural networks, etc.) and experience with Python ML tools (e.g., scikit-learn, sparkML and pySpark, tensorflow, keras, PyTorch)
- Experience with relational SQL and NoSQL databases, including SQL Server, MySQL and Cassandra
- Savvy with data science stack (Pandas, NumPy, SciPy)
- Understanding of Data Structures and Algorithms
- Unix/Linux command-line experience
- Strong Linear Algebra, convex optimization is a plus
- Data Science/Analysis background; Proficient at working with large datasets
- Familiarity with quantitative finance concepts such as portfolio optimization, option pricing, backtesting
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift, Athena, SQS, etc.
- Broad understanding of equities, derivatives, futures, and FX products
- Experience researching, designing, developing and deploying factor models, alpha signals, portfolio optimizers, pricers, or trading algorithms.
- Knowledge of Agile/Scrum methodologies
- Results-oriented, can deliver quality code quickly
- Highly analytical with good problem solving skills
- BA/BS/MS/PhD degree in Computer Science, Statistics, Applied Math, Financial Engineering or equivalent
- Excellent listening, and communication (both oral and written) skills
- Self-starter and critical thinker, takes ownership of own projects and makes improvement suggestions for the entire infrastructure.
- Proactive, assertive and attentive to details.
- Can work independently and in a collaborative environment.
- Can handle several projects with different priorities at the same time in a fast-paced environment.
- Excellent self-management and problem-solving skills. Quick learner