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Contract Causal Inference Jobs in Long Beach, CA

1 point system

Data Engineer

Los Angeles, CA · On-site

$60/hr

... Contract Rate $60/hr. on W2 * Serve as developer of key DTC analytical models like customer ... testing, and causal inference. * Strong skills in feature engineering, handling large-scale ...

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Contract Causal Inference information

What is a contract causal inference specialist?

A Contract Causal Inference specialist is a professional who applies statistical and analytical methods to determine cause-and-effect relationships within data, typically on a contractual or project basis. These specialists are often brought in to analyze business, healthcare, or social science data to help organizations make evidence-based decisions. They use techniques such as randomized controlled trials, regression analysis, and propensity score matching to isolate causal impacts. Contract roles are usually temporary and focused on specific projects or questions. This position requires strong statistical knowledge, programming skills, and the ability to communicate findings to non-technical stakeholders.

What are the key skills and qualifications needed to thrive as a contract causal inference specialist?

To thrive as a Contract Causal Inference Specialist, you need a strong background in statistics, econometrics, or data science, typically with an advanced degree in a quantitative field. Proficiency with statistical software like R, Python, and specialized causal inference packages, as well as experience with data wrangling tools, is essential. Exceptional analytical thinking, clear communication, and attention to detail are valuable soft skills for interpreting results and collaborating with clients. These competencies are vital for delivering robust, actionable insights that drive evidence-based decision-making in a contractual setting.

What are some common challenges faced by professionals in contract causal inference roles, and how can they be addressed?

Professionals in contract causal inference roles often encounter challenges such as working with incomplete or messy datasets, ensuring the validity of assumptions in causal models, and effectively communicating complex findings to stakeholders. Addressing these issues typically involves using robust statistical techniques, performing thorough data cleaning, and engaging in transparent documentation of the modeling process. Additionally, collaborating closely with subject matter experts and stakeholders can help clarify project goals and improve the relevance and impact of your analyses.

What is the difference between Contract Causal Inference vs Data Analyst?

AspectContract Causal InferenceData Analyst
Required CredentialsStatistics, Data Science, or related certifications; often advanced degreesBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch-focused, project-based, often in consulting or academiaBusiness environments, analyzing data to inform decisions
Employer & Industry UsageResearch institutions, consulting firms, tech companiesCorporations, marketing agencies, finance, healthcare
Search & Comparison IntentUnderstanding causal relationships, research projectsData analysis, reporting, business insights

Contract Causal Inference specialists focus on identifying cause-and-effect relationships through research and statistical methods, often in consulting or academic settings. Data Analysts interpret data to generate reports and insights for business decisions. While both roles require data skills, Contract Causal Inference emphasizes causal modeling and research, whereas Data Analysts focus on descriptive and diagnostic analysis.

What job categories do people searching Contract Causal Inference jobs in Long Beach, CA look for?

The top searched job categories for Contract Causal Inference jobs in Long Beach, CA are:

What cities near Long Beach, CA are hiring for Contract Causal Inference jobs?

Cities near Long Beach, CA with the most Contract Causal Inference job openings:

Contract Causal Inference jobs near you
Infographic showing various Contract Causal Inference job openings in Long Beach, CA as of June 2026, with employment types broken down into 28% Full Time, 2% Part Time, 2% Temporary, and 68% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution.

Data Engineer

1 point system

Los Angeles, CA • On-site

$60/hr

Contractor

Re-posted 17 days ago

Job description

Job Title

Data Engineer

Client

Confidential

Location

Los Angeles, CA (5 days - Onsite)

Type of Hire

Long Term Contract

Rate

$60/hr. on W2

Job Description:

  • Serve as developer of key DTC analytical models like customer lifetime value, attribution, churn, and AB testing
  • Own end-to-end model development, from scoping → exploration → feature engineering → model development → validation → deployment.
  • Work closely with data engineering and product teams to operationalize models, ensuring scalability, reproducibility, and automated monitoring.
  • Conduct deep-dive analyses to uncover insights that inform content strategy, product experience, and growth plans for the service.
  • Translate complex modeling results into clear, compelling narratives for leadership and cross-functional teams.
  • Work closely with product, marketing, and platform teams to identify opportunities for advanced analytics and modeling.
  • Partner with Insights Strategy & Analytics dedicated Core team (BI, data engineering, and Strategic Analysts) and leadership to integrate modeling outputs into data products, dashboards, and business-embedded tools that support decision-making across the client's Core ecosystem.

 
Excellent Communication
 
Qualifications

  • 7+ years of experience in data science, ideally in streaming, digital media, consumer apps, or subscription businesses.
  • Proven track record developing predictive models, experimentation frameworks, and advanced analytics for DTC or digital platforms.
  • Expert proficiency in Python and SQL.
  • Hands-on experience with experimentation platforms, uplift modeling, statistical testing, and causal inference.
  • Strong skills in feature engineering, handling large-scale behavioral data, and building ML pipelines.
  • Experience with cloud-based environments (AWS, GCP, Databricks) and MLOps practices
  • Strong understanding of the TV and streaming landscape across linear, digital, AVOD, FAST, SVOD, and emerging platforms
  • Strong communicator capable of presenting complex modeling outputs to non-technical audiences.
  • Ability to operate in ambiguity and help stakeholders articulate questions, opportunities, and hypotheses.
  • Passion for streaming, entertainment, consumer behavior, and data-driven storytelling.
  • Highly collaborative, curious, and eager to partner across functions