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LinQ Global Group

Data Scientist

Pay: Not specified

Posted: 8 weeks ago

Location: Glendale, CA (Onsite)

Last Updated: 2 weeks ago

Hours: Full-Time

Expires: 9/27/2026

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What they do

A Data Scientist utilizes skills and experience to systematically answer questions using data to provide actionable recommendations. Commonly utilizes advanced statistical analysis and machine learning techniques. Common responsibilities also include data cleaning and data management.

$138,705 / year median in California

+8% projected growth

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Job Description

Data Scientist LinQ Global Group Glendale, CA Job Details Full-time 1 day ago Qualifications AI models Quantitative applied research Design of experiments Research project design Machine intelligence Inferential statistics Statistical modeling A/B testing Machine learning frameworks Stakeholder relationship building Statistical analysis tools Stakeholder management

Full Job Description Job Title:

Data Scientist Location:

Glendale, CA, 91201

Job Type:

Full-Time Job Summary We are looking for an experienced Data Scientist to design and analyze A/B tests and causal inference studies. You will work with cross-functional teams to generate insights, improve business decisions, and build scalable experimentation solutions using advanced statistical methods. Responsibilities Design and execute A/B tests and geo experiments. Analyze data using statistical and causal inference techniques. Build scalable experimentation and analytics solutions. Develop statistical models and machine learning solutions. Perform sample size calculations, power analysis, and experiment evaluation. Present findings and recommendations to business stakeholders and leadership. Collaborate with cross-functional teams to solve business problems. Mentor team members and promote best practices in experimentation. Required Qualifications Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, Engineering, or a related quantitative field. 7+ years of experience in experimentation, causal inference, or data science. Strong knowledge of A/B testing, experimental design, and statistical modeling. Experience with causal inference methods such as Difference-in-Differences, Propensity Score Matching, and Instrumental Variables. Proficiency in Python and/or R. Experience with machine learning libraries such as scikit-learn or LightGBM (LGBM). Strong analytical, problem-solving, and communication skills. Preferred Qualifications Master's or PhD in a quantitative field. Experience with ETL processes and data engineering. Familiarity with Databricks, Snowflake, Jupyter, and GitHub. Experience deploying data science solutions in production. Strong leadership and stakeholder management skills.