Data Scientist ( Los Angeles-California )
At a glance
Mid-level Data Science role at GSB Solutions. Los Angeles · full-time · no salary stated · we estimate $125,676–$151,163.
GSB Solutions has not published a salary for this role. The figure below is our estimate, not theirs.
dataroles summary, based on the employer's posting.
What you'll do
- Build predictive and machine learning models for financial and operational needs, then put them into production
- Create data models and reliable pipelines, coordinating with engineering on the telemetry they require
- Trace large datasets for patterns and explain model findings through visualizations to business and technical audiences
- Track model performance and help keep deployed machine learning systems reliable and maintainable
- Guide other engineers and share data practices with leadership
What you bring
- More than five years delivering data science projects, with clear experience building machine learning models
- A bachelor’s degree in a quantitative discipline such as computer science, statistics or mathematics
- Programming ability in Python, R or Scala, plus strong command of scikit-learn, numpy, pandas and other ML libraries
- Experience taking machine learning pipelines from data extraction and feature work through testing and deployment
- Strong grounding in machine learning, statistics and mathematics, with the ability to explain findings to decision-makers
Who this fits
This role suits a hands-on data scientist who can build models and help operationalize them with engineering teams. It is based on-site in Los Angeles, runs from 8:00 AM to 5:00 PM, and is a six-month contract. The posting specifies a master’s degree as the education level.
From the employer
We are looking for a Data Scientist with more than 5 years of experience.
Key Responsibilities:
● Develop novel AI/ML solutions to further the company’s mission of creating innovative and engaging content
● Architect efficient data models and high-quality production pipelines and partner with Engineering for all necessary telemetry
● Design, build, and deploy predictive models, machine learning algorithms, and statistical analyses to address complex business challenges.
● Identify trends, patterns, and insights from large datasets to inform decision-making.
● Work end to end from data collection, feature generation and selection, algorithm development, forecasting, visualization and communicating of model results
● Think creatively to solve complex problems
● Monitor and maintain the performance of ML models
● Research and stay up-to-date on the latest AI/ML trends and technologies
● Provide technical guidance and mentorship to other engineers
● Collaborate with data engineering teams to ensure the quality and accessibility of data
● Communicate insights and best practices in leadership
Qualifications:
● Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related quantitative field (Master’s degree a plus)
● 5+ years of experience in data science, with a track record of delivering successful projects
● Proficiency in programming languages such as Python, R, or Scala
● Expert-level experience working with scikit-learn, numpy, and pandas and other ML libraries.
● Solid understanding of ML technologies, models, mathematics and statistical methods
● Expert data-driven storytelling skills to convey insights to business leaders and technical stakeholders and to drive impactful decisions, with an eye for great ways to visualize data
● Excellent problem-solving skills and the ability to think creatively
● Experience building and deploying full stack ML pipelines: data extraction, data mining, model training, feature development, testing, and deployment
● Experience with financial forecasting models is a plus
● Experience with cloud databases, such as Snowflake, databricks, and BigQuery is a plus
● Familiarity with data processing tools like dbt and Airflow, UI layers like Streamlit is a big plus
What does a typical day look like?
Machine Learning Development
The candidate will:
• Develop machine learning models.
• Support financial and operational business use cases.
• Design advanced analytical solutions.
Productionization of Models
An important distinction was made between:
Building models.
Operationalizing models.
Responsibilities include:
• Deploying machine learning solutions.
• Supporting ML Operations (MLOps).
• Working with engineering teams.
• Creating solutions that are repeatable, maintainable, and scalable.
• Contributing to Snowflake-based environments.
Based on the job description, tell me what the top 5 must have skills needed for this role?
Must-Have Skills
Machine Learning experience.
Python.
Snowflake.
MLOps experience.
Additional emphasis:
• Machine learning expertise was repeatedly identified as the most important qualification.
• The manager indicated candidates should clearly demonstrate experience building ML models.
• Other emerging AI technologies can be learned, but foundational machine learning experience is required.
Other Requirements:
Location: Los Angeles, California
Remuneration: Payment would be based on hours worked.
Education Level: Master’s Degree
Schedule: 8:00 AM – 5:00 PM
Experience: 5+ years
Work Model: On-site
Contract: 6 months
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