Data Scientist

SFE; Glendale (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

SFE is seeking a Senior Data Scientist in Glendale, CA to develop AI/ML solutions and productionize models that drive innovative content. You will collaborate across data engineering and engineering to build scalable pipelines and deliver data-driven insights.

You should have 5+ years in data science, strong Python/R/Scala skills, and a proven track record deploying ML systems. Hybrid cloud tooling and analytics experience are a plus.

Qualifications

• Bachelor's degree in a quantitative field; Master's preferred.
• 5+ years of experience in data science with a track record of delivering successful projects.
• Proficiency in Python, R, or Scala.
• Expert with scikit-learn, NumPy, and pandas and other ML libraries.
• Solid understanding of ML techniques, models, math and statistics.
• Strong data-driven storytelling to convey insights to leaders and stakeholders.
• Experience building and deploying full-stack ML pipelines (data extraction, modeling, deployment).
• Experience with cloud databases such as Snowflake, Databricks, and BigQuery.

Responsibilities

• Develop novel AI/ML solutions to drive the company's mission of innovative content.
• Architect data models and production pipelines; ensure telemetry with Engineering.
• Design, build, and deploy predictive models and ML algorithms for business challenges.
• Identify trends and insights from large datasets to inform decisions.
• End-to-end workflow: data collection, feature generation, modeling, forecasting, visualization, and presenting results.

Skills

Machine Learning

Python

MLOps

Data storytelling

Education

Bachelor's degree in CS/Statistics/Math/Data Science

Tools

Snowflake

Databricks

BigQuery

dbt

Airflow

Streamlit

Job description

Title: Senior Data Scientist

Openings: 1

Contract Length: 1 year

Start Date: 10/2/2026 - End Date: 10/2/2027

Location: Glendale, CA

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

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Tell me what this person will be doing day to day? 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:

1. Building models.
2. 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

1. Machine Learning experience.
2. Python.
3. Snowflake.
4. 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.