Associate Data Scientist

Join Quantifind as an Associate Data Scientist, where you'll prototype and build complex Machine Learning solutions, improve existing products through data-driven development cycles, and support customers in maximizing the value of our Graphyte platform. You'll collaborate with Product Managers and Platform Engineers, analyze large unstructured data sets, design and maintain ETL pipelines, train machine learning models, and implement Data Science solutions in our Production Scala codebase. Enjoy meaningful equity, performance reviews, collaboration across departments, and flexible work options.

• Prototyping and building complex Machine Learning solutions, improving existing products through data-driven development cycles.
• Collaborating with team members and key stakeholders to explore ideas, test hypotheses, and prototype solutions.
• Leveraging SQL, Python, and PySpark to analyze large unstructured data sets, designing and maintaining ETL pipelines.

• You are excited to apply your existing expertise in fields such as statistics and computer science to solve mission critical problems
• You are passionate about maintaining the high scientific and engineering standards required to enable your peers
• You are a quantitative thinker who wants to develop further as both a data scientist and an engineer
• Above all, you are a curious and independent problem solver who is motivated to find a place where your skills can have real impact
• You share Quantifind’s commitment to winning together, and are eager to see your coworkers build on the technical foundations you will be creating
• You are excited to work at a fast-paced startup where you will have a chance to expand your scientific and engineering skills to new areas
• You are skilled at finding the precise mathematical kernels of real-world problems and want to bring that talent to bear on the business questions facing the world’s leading financial services companies
• Experience with SQL and/or Spark
• At least 1 year of professional industry experience, in addition to your academic experience
• Experience using supervised and unsupervised statistical techniques such as regression, classification, and clustering
• Strong programming experience in Python and one or more of the following: Scala/Java or R
• MS or higher in the following areas: Statistics, Mathematics, or Computer Science
• Outstanding analytical skills and the ability to communicate quantitative results to technical and non-technical audiences
• Experience with Applied NLP methods is a strong plus, including topic modeling, text classification, word embeddings, and named entity extraction
• Knowledge of data structures and algorithm complexity
• Strong knowledge of Statistics/Probability/Machine Learning including core concepts of hypothesis testing, inference, bias-variance trade-off, regularization, dimensionality reduction etc
• Experience with popular machine learning algorithms such as random forests, Boosting, and neural networks