Data Scientist ( Los Angeles-California )

GSB; Los Angeles (CA); On-site; USD 55,000 - 96,000; Full time

Job summary

GSB in Los Angeles is seeking a Data Scientist with 5+ years of experience to develop AI/ML solutions and build scalable production pipelines. You will collaborate with Engineering and Data teams to deploy models, generate actionable insights, and communicate results to leadership.

The role emphasizes on-site work, strong Python-based ML skills, and a track record of delivering data-driven business impact. Prior experience with Snowflake and cloud tools is a plus.

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

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
• Deploying machine learning solutions
• Working with engineering teams
• Creating solutions that are repeatable, maintainable, and scalable
• Contributing to Snowflake-based environments

Skills

ML experience

Python

Education

Bachelor’s degree in Computer Science or related field

Tools

Snowflake

Job description

• On-site
• Human Capital

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?

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:

Responsibilities include:

• Deploying machine learning solutions.
• 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.
• Additional emphasis:

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:

Remuneration Payment would be based on hours worked.