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Remote Python Trading Jobs in Compton, CA (NOW HIRING)

Sr. Database Administrator

Los Angeles, CA · On-site +1

$120K - $145K/yr

San Diego, CA Irvine, CA Los Angeles, CA Centennial, CO Las Vegas, NV Remote or Hybrid is not ... Automate Database server maintenance tasks through TSQL, PowerShell, and Python * Hands-on ...

Remote Python Trading information

See Compton, CA salary details

$13

$59

$87

How much do remote python trading jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for remote python trading in Compton, CA is $59.54, according to ZipRecruiter salary data. Most workers in this role earn between $49.09 and $67.64 per hour, depending on experience, location, and employer.

What is a Remote Python Trading job?

A Remote Python Trading job involves developing, maintaining, and optimizing trading algorithms or systems using the Python programming language, all while working remotely. Professionals in this role typically work for financial institutions, hedge funds, or fintech companies, analyzing market data, building automated trading strategies, and ensuring their code runs efficiently and securely. Strong programming skills in Python, knowledge of financial markets, and experience with trading platforms or APIs are essential. The remote nature of the job allows professionals to work from anywhere with a reliable internet connection.

What is the difference between Remote Python Trading vs Remote Quantitative Analyst?

AspectRemote Python TradingRemote Quantitative Analyst
Required CredentialsPython programming, finance knowledge, data analysis skillsMathematics, statistics, programming, finance or economics degree
Work EnvironmentFinancial firms, hedge funds, trading companiesFinancial institutions, investment firms, research organizations
Industry UsageHigh in trading and algorithm developmentHigh in risk modeling and quantitative research
Common Search/ComparisonYesYes

Remote Python Trading focuses on developing trading algorithms using Python, primarily in trading firms. Remote Quantitative Analysts work on financial modeling and risk analysis, often requiring similar skills but with a broader focus on quantitative research. Both roles involve programming and finance, but their core responsibilities differ in application and industry emphasis.

What are the key skills and qualifications needed to thrive as a Remote Python Trading professional, and why are they important?

To thrive as a Remote Python Trading professional, you need strong proficiency in Python programming, quantitative analysis, and a solid understanding of financial markets, often supported by a relevant degree in finance, mathematics, or computer science. Experience with trading platforms, APIs, backtesting frameworks, and familiarity with libraries like pandas, NumPy, and scikit-learn are typically required. Analytical thinking, problem-solving, and effective remote communication are essential soft skills for success in this role. These skills enable the development of robust trading algorithms, effective risk management, and seamless collaboration in a distributed work environment.

What are some common challenges faced by remote Python trading developers, and how can they be addressed?

Remote Python trading developers often encounter challenges such as managing effective communication with distributed teams, ensuring code reliability in automated trading systems, and keeping up with rapidly evolving market requirements. To address these, it’s important to establish clear communication channels (such as daily stand-ups or regular check-ins), write well-documented and thoroughly tested code, and stay updated on current trading technologies and market regulations. Additionally, leveraging collaborative tools like version control systems and implementing robust monitoring for trading algorithms helps ensure both team alignment and system stability.
What cities near Compton, CA are hiring for Remote Python Trading jobs? Cities near Compton, CA with the most Remote Python Trading job openings:
Real Estate Data Scientist - Remote

Real Estate Data Scientist - Remote

Harbor Freight Tools

Calabasas, CA • On-site, Remote

$98K - $147K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 20 days ago


Job description


The Real Estate Data Scientist is responsible for developing advanced analytical models and data-driven tools that support strategic real estate decisions across the organization. This role partners closely with Real Estate, Finance, Marketing, and Supply Chain teams to deliver predictive insights related to site selection, network optimization, sales forecasting, and market planning. This role incorporates advanced spatial modeling, geostatistics, and geospatial data engineering to evaluate trade areas, quantify market potential, and optimize network performance.
This position combines strong statistical modeling, data engineering, and business acumen to translate complex data into actionable recommendations. The Real Estate Data Scientist plays a critical role in advancing the organization's use of machine learning, automation, and predictive analytics to improve decision quality and scalability. This is a senior individual contributor role with no direct people management responsibility.
Duties and Responsibilities
  • Advanced Analytics & Predictive Modeling
    • Develop and deploy predictive models for site selection, sales forecasting, cannibalization, and market potential.
    • Build and maintain machine learning models using regression, classification, clustering, optimization, and spatial modeling techniques.
    • Apply spatial statistical methods (e.g., spatial regression, geographically weighted regression, spatial autocorrelation) to capture geographic variation in demand drivers.
    • Develop trade area and customer draw models (e.g., Huff/gravity models) to estimate market share and competitive impact.
    • Incorporate spatial features such as proximity, co-tenancy, demographics, traffic patterns, and nearby store performance into predictive models.
    • Design methodologies for forecasting store performance under various scenarios, including spatial and competitive effects.
    • Continuously monitor and improve model performance and accuracy.
  • Data Engineering & Automation
    • Design scalable data pipelines integrating real estate, customer, demographic, sales, and geospatial datasets (parcel, census, traffic, mobility, POI data).
    • Perform geospatial data processing including geocoding, spatial joins, coordinate transformations, and spatial indexing (e.g., H3 or similar frameworks).
    • Write efficient SQL and Python workflows to automate recurring analyses, spatial feature engineering, and model refreshes.
    • Ensure data quality, consistency, and reproducibility across analytical outputs, including alignment of spatial boundaries and geographic hierarchies.
  • Real Estate Strategy & Decision Support
    • Partner with Real Estate teams to support site selection, market entry, relocations, and closures.
    • Develop drive-time and network-based trade area analyses to assess accessibility and market reach.
    • Conduct market coverage and white space analysis to identify expansion opportunities and underserved areas.
    • Build location-allocation and network optimization models to determine optimal site placement.
    • Quantify cannibalization and competitive effects using spatial overlap and proximity-based modeling.
    • Provide quantitative insights for Real Estate Committee (REC) evaluations and executive decisions.
    • Develop scoring frameworks and decision tools to prioritize opportunities.
  • Visualization & Communication
    • Create clear, compelling visualizations and dashboards (Tableau, Power BI, or similar) to communicate insights.
    • Develop interactive geospatial visualizations including trade area maps, performance heatmaps, and market opportunity analyses.
    • Present analytical findings and recommendations to senior leadership and non-technical stakeholders.
  • Experimentation & Innovation
    • Design and execute experiments (A/B tests, quasi-experimental designs) to evaluate real estate strategies.
    • Implement geo-based testing frameworks (e.g., test vs. control markets) to measure impact of site decisions.
    • Apply causal inference methods (e.g., difference-in-differences, synthetic control) accounting for geographic spillovers.
    • Explore new data sources (e.g., mobility, foot traffic) and modeling techniques to enhance predictive capabilities.
    • Contribute to building a best-in-class real estate analytics capability.
  • Cross-Functional Collaboration
    • Work closely with GIS, Data Engineering, Finance, Marketing, and IT teams to align data and models.
    • Partner with GIS teams to ensure alignment between spatial analysis, mapping, and production data pipelines.
    • Translate business problems into analytical solutions and actionable insights.
Scope
  • Staff supervision and development: No
  • Decision making:
    • Develops models and analytical frameworks used in strategic decision-making
  • Travel: Up to 10%
  • Flex Designation: Anywhere

The anticipated salary range for this position is $98,500-$147,800 depending on location, knowledge, skills, education and experience. This position is also eligible for an annual discretionary bonus. In addition, we offer comprehensive and competitive benefits to Associates (and their families) such as medical, dental, vision, life insurance, short-term and long-term disability. Eligible Associates are able to enroll in our company's 401k plan. Associates will accrue paid time off up to 236 hours per year (inclusive of PTO, floating holidays, and paid holidays). Paid sick time up to 80 hours per year unless otherwise required by law.
Requirements
Education and Experience
Education Requirements
  • Bachelor's degree in data science, Statistics, Economics, Mathematics, Computer Science, or related field from a nationally recognized institution. Master's degree preferred
Years of Experience
  • 5 to 8 plus years of experience in data science, analytics, or quantitative modeling, preferably in retail, real estate, consulting, or related fields.
Skills
  • Strong proficiency in Python (pandas, scikit-learn, etc.) and SQL for data analysis and modeling.
  • Experience building predictive models and applying statistical techniques to business problems.
  • Experience working with cloud-based platforms (Databricks, Snowflake, Azure)
  • Familiarity with geospatial analysis and GIS concepts, including trade area modeling, spatial statistics, and network-based analysis (experience with ESRI or similar tools preferred).
  • Experience working with large, complex datasets from multiple sources.
  • Experience with BI and visualization tools (Tableau, Power BI, etc.).
  • Strong understanding of experimental design and statistical inference.
  • Ability to communicate complex analyses clearly to non-technical stakeholders.
  • Strong problem-solving skills and business acumen.
Physical Requirements
Corporate - Remote - General office environment requiring ability to:
  • Stand, walk, sit for extended periods of time .
  • Speak and listen to others in person and over the phone and video conferencing.
  • Use keyboard and read from computer screen and reports.
  • The ability to lift up to 15 lbs.
Safety
Must be able to perform this job safely in accordance with standard operating procedures and good manufacturing practices, without endangering the health or safety of self or others.
About Harbor Freight Tools
We're a 45 year-old, $8 billion national tool retailer with the energy, enthusiasm, and growth potential of a start-up. We have over 1,600 stores in 48 states across the country and are opening several new locations every week. We offer our customers more than 7,000 tools and accessories, from hand tools and generators to air and power tools, from shop equipment to automotive tools. We provide our customers with the right tool for the right job at the right price, always delivering quality and value.