About this role
Financial institutions and government agencies struggle with compliance processes that demand increasing human resources while managing anti-money laundering, fraud, and risk management. Quantifind addresses this challenge by developing machine learning driven solutions that combine internal financial data with public domain text sources to uncover risk signals through a SaaS platform.
As an Associate Data Scientist based in Palo Alto, this hire will prototype complex machine learning solutions, build ETL pipelines, and leverage large language models to scale data science tasks. Working closely with product management and platform engineering, the team translates unstructured data into accurate risk assessments for leading financial services clients.
An ideal candidate brings quantitative rigor, an interest in bridging data science and software engineering, and a collaborative approach to problem-solving. This role suits independent thinkers who thrive in an agile startup environment and want to build technical foundations that empower their peers and support key customers.
What you will do
- Collaborate with team members and stakeholders to explore ideas, test hypotheses, and prototype solutions in an agile environment.
- Leverage SQL, Python, and PySpark to analyze large unstructured datasets and inform research directions or modeling tasks.
- Design, write, and maintain ETL pipelines for integrating complex datasets into the platform.
- Train machine learning models and implement data science solutions in the production Scala codebase following software engineering best practices.
- Utilize large language models to scale data science workflows such as data labeling and structured information extraction.
- Participate in code reviews and experiment with novel ways to apply existing data-based solutions to unique customer challenges.
What you need
- Hold an MS or higher degree in Statistics, Mathematics, or Computer Science.
- Possess at least one year of professional industry experience alongside academic background.
- Demonstrate strong knowledge of statistics, probability, and machine learning core concepts.
- Show hands-on experience using supervised and unsupervised statistical techniques and popular machine learning algorithms.
- Exhibit strong programming experience in Python and at least one of Scala, Java, or R.
- Bring practical experience with SQL, Spark, and data structures with an understanding of algorithm complexity.
Nice to have
- Experience with Applied NLP methods including topic modeling, text classification, word embeddings, and named entity extraction
Benefits
- Competitive salary
- Company Equity
- Exceptional benefits package
- Flexible Vacation & Paid Time Off
- Employer-matched 401(k) plan
- Lunch provided for employees in the Palo Alto office
Skills and tech stack
Questions candidates ask
What is the remote work policy?
The development team is centered in Palo Alto, California, with technology hubs in Atlanta and Washington, D.C. The company currently uses a hybrid mix of working from home and in the office.
What is the salary range for this position?
The base salary range for this full-time position is $100,000 to $130,000. Individual pay is determined by factors including work location, role-related knowledge, skills, and depth of experience.
What tools and languages will I use?
The tech stack includes SQL, Python, PySpark, and Spark for data analysis and pipeline building. Team members also implement solutions in a production Scala codebase and leverage large language models.
What kind of team will I be working with?
You will join the Data Science team and work closely with Product Management and Platform teams in an agile environment. The company provides a supportive environment that fosters collaboration and professional growth.