Associate Data Scientist Job Los Angeles area,California USA,IT/Tech

Members of the Data Science team prototype and build complex Machine Learning solutions, improve and refine existing products through data-driven development cycles, and support our customers extract the maximum value out of Quantifind’s Graphyte platform through proofs of concepts (POC) and purpose built solutions as necessary
We work closely with the Product Management and Platform teams to anticipate company needs and quickly put state-of-the-art Data Science and AI tools into the hands of end users
Collaborating with fellow team members and key stakeholders, such as, Product Managers, Platform Engineers to explore ideas, test hypotheses, and prototype solutions
Working in an agile environment breaking down complex problems into smaller manageable tasks with the help of your teammates and manager
Leveraging SQL, Python and PySpark to analyze large unstructured data sets to answer key business questions, inform research directions, or set up modeling tasks
Designing, writing, and maintaining ETL pipelines for integrating large and complex datasets
Experimenting with novel ways to use existing data-based solutions to support customers’ unique challenges
Training machine learning models to solve complex problems
Implementing Data Science solutions in our Production Scala codebase following software engineering best practices
Leveraging Large Language Models (LLMs) to scale up various data science tasks (for example: data labeling, extracting structured information, …)
Participating in code reviews

Benefits

Meaningful equity to full-time employees
Performance reviews conducted twice per year, with opportunities to advance
Collaboration across departments - there’s always an opportunity to work on the projects you care most about
We encourage people to hone their crafts by taking classes and attending conferences
We pay 95% of your premiums with top medical, dental and vision plans for you and your family, plus other benefits including FSAs and life insurance
We match employee retirement contributions dollar-for-dollar up to 4% after your first year
Flexible hours and a flexible vacation policy
Remote or in-office options

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 RMS 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