Data Scientist

Quantifind•Palo Alto, CA

6d•Hybrid

About The Position

Quantifind is seeking to fill a Data Scientist position on our Data Science team. We work closely with the Product Management team and Platform engineers to anticipate company needs and quickly put state-of-the-art mathematical tools into the hands of end users. Members of the Data Science team translate real-world problems into quantitative language, find or create algorithms to solve those problems, and implement them in code. Our team values a creative and empathetic approach to problem-solving and strives to maintain rigorous scientific and engineering standards. We will give you the opportunity to work on the full spectrum of data science challenges, bringing solutions from research all the way to production.

Requirements

Master’s degree or higher in Statistics, Mathematics, Computer Science, or a related quantitative field.
At least 2 years of professional industry experience, in addition to academic experience.
Proficient in two or more of the following: Scala / Java, Python, R.
Outstanding quantitative and analytical ability.
Able to take less-than-precise business requirements and translate them into quantitative problems.
In-depth knowledge of Statistics / Probability / Machine Learning, including foundations such as bias/variance trade-off, regularization, dimension reduction, and model explanation.
Ability to apply software engineering best practices to build scalable, reliable ML pipelines.
Comfortable prototyping algorithms, iterating quickly, and working collaboratively.
Prior experience working with large-scale datasets (Millions of records) using SQL and Spark.
Excellent written and verbal communication skills.
Ability to distill complex concepts into clear and effective verbal and written presentations.
Strong critical thinker and knows how to problem solve.
Deep sense of personal accountability for work product quality.
Positive attitude even in a deadline-driven environment.

Nice To Haves

Prior experience with Natural Language Processing (NLP) methods such as Word and Contextual Embeddings, Named Entity Recognition, Topic Modeling, large-scale Document Classification, and Sequence-to-Sequence Models.

Responsibilities

Finding the precise mathematical kernels of real-world business challenges faced by leading international financial institutions.
Applying expertise in statistics and computer science using Quantifind’s state-of-the-art infrastructure to solve problems in Natural Language Processing, such as Entity Resolution, Document Classification, building Knowledge Graphs, and Topic Modeling.
Translating real-world problems into quantitative language.
Finding or creating algorithms to solve problems.
Implementing algorithms in code.
Working on the full spectrum of data science challenges, bringing solutions from research all the way to production.
Working closely with Sales, Product, and Technology teams to promote a Customer Centric culture.
Delighting clients at some of the world’s leading Financial Institutions, helping them identify financial crimes.