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Python For Finance Jobs in California (NOW HIRING)

Together AI

Finance Analytics Engineer

San Francisco, CA · On-site

$200K - $240K/yr

You will own the data layer that Finance runs on - building from scratch the models, pipelines, and ... Python for data tooling: automation, data quality frameworks, custom dbt macros or operators.

Together AI

Finance Analytics Engineer

San Francisco, CA · On-site

$200K - $240K/yr

You will own the data layer that Finance runs on - building from scratch the models, pipelines, and ... Python for data tooling: automation, data quality frameworks, custom dbt macros or operators.

PTR Global

Python Developer

San Francisco, CA · On-site

$59.25 - $81.50/hr

The team is responsible for modernizing a core mainframe-based financial application by rewriting ... This role is heavily backend-focused, with strong emphasis on Python and PySpark, while also ...

Apple

Finance Data Scientist - Enablement

Cupertino, CA · On-site

$141K - $213K/yr

Transitioning from manual or local processes into to governed, automated workflows in Dataiku SQL and Python fundamentals for Finance analysts No-code/low-code entry points with visual recipes Prompt ...

Apple

Data Engineer, Operations Finance

Sunnyvale, CA · On-site

$134K - $161K/yr

... Python for data pipelines and automation Experience with scheduling systems and CI/CD tools such as ... Finance and Accounting process knowledge is a plusExcellent communication skills and ability to ...

McGuireWoods LLP

Sr. Financial Systems Analyst

San Francisco, CA · On-site +1

$101K - $137K/yr

... for administration and support of the firm's accounting and finance applications. This includes the ... Python experience preferred. * Experience using Python for data extraction, transformation, and ...

McGuireWoods LLP

Sr. Financial Systems Analyst

Los Angeles, CA · On-site +1

$95K - $128K/yr

... for administration and support of the firm's accounting and finance applications. This includes the ... Python experience preferred. * Experience using Python for data extraction, transformation, and ...

Anthropic

Finance & Strategy, Compute

San Francisco, CA · On-site

$100K - $125K/yr

Passion for Anthropic's mission to build safe, transformative AI systems Preferred qualifications ... Proficiency with SQL, Python, and Excel * Prior chief-of-staff, BizOps, or finance-systems ...

Stripe

Finance & Strategy Analyst

San Francisco, CA · On-site

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of ... Python or a willingness to learn • Experience in data visualization and dashboarding

SprintRay

Finance Systems Lead

Los Angeles, CA

$150K - $180K/yr

Python development experience within Odoo framework * Experience with SQL for financial data queries and reporting * Knowledge of ERP integrations and data migration * Familiarity with BI tools ...

Extractable

Python Integrations Developer

San Francisco, CA · Remote

$59.25 - $81.50/hr

The Role We're looking for a Python Integrations Developer to own and expand the third-party integrations that connect our platform with the systems financial institutions rely on every day. You'll ...

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Python For Finance information

What is the difference between Python For Finance vs Quantitative Analyst?

AspectPython For FinanceQuantitative Analyst
Required CredentialsPython skills, finance knowledge, possibly finance-related certificationsAdvanced degrees (e.g., MSc, PhD) in finance, mathematics, or related fields; certifications like CFA
Work EnvironmentFinancial firms, trading desks, investment banks, hedge fundsFinancial institutions, hedge funds, asset management firms, consulting
Employer & Industry UsageUsed for developing trading algorithms, risk modeling, data analysisDevelops quantitative models, risk assessments, trading strategies

Python For Finance focuses on using Python programming to analyze financial data and develop models, often as a technical skill. Quantitative Analysts, however, apply advanced mathematical and statistical techniques to create complex financial models. While both roles require strong analytical skills, Quantitative Analysts typically have higher-level degrees and certifications, and their work involves more theoretical modeling. Python For Finance is often a skill within a Quantitative Analyst's toolkit, but the roles differ in scope and depth.

How does a Python for Finance professional typically collaborate with other departments within a financial organization?

Python for Finance professionals frequently work alongside departments such as data analytics, risk management, and portfolio management. They often translate complex financial models into scalable code, automate data processes, and support decision-making by providing actionable insights through data analysis. Effective communication and collaboration are essential, as these professionals must understand the specific needs of stakeholders and ensure that technical solutions align with business objectives. Regular meetings, code reviews, and cross-functional project teams are common structures within the work environment.

What is Python for Finance?

Python for Finance refers to the use of the Python programming language for financial analysis, modeling, trading, and data visualization. Financial professionals use Python to automate data processing, analyze large financial datasets, build quantitative models, and develop trading algorithms. Its vast ecosystem of libraries such as Pandas, NumPy, and Matplotlib makes Python a popular choice in the finance industry for tasks ranging from risk management to portfolio optimization.

What are the key skills and qualifications needed to thrive as a Python Developer in Finance, and why are they important?

To thrive as a Python Developer in Finance, you need strong programming skills in Python, a solid understanding of financial concepts, and often a degree in computer science, finance, or a related field. Familiarity with financial libraries (such as pandas, NumPy, and QuantLib), databases, and version control systems is typically required, and certifications in data science or finance can be advantageous. Analytical thinking, attention to detail, and effective communication are vital soft skills for interpreting financial data and collaborating with cross-functional teams. These skills are essential to develop robust financial solutions, ensure data accuracy, and drive informed decision-making in a highly regulated and data-driven industry.
What cities in California are hiring for Python For Finance jobs? Cities in California with the most Python For Finance job openings:
Python For Finance jobs near you

Finance Analytics Engineer

Together AI

San Francisco, CA • On-site

$200K - $240K/yr

Full-time

Medical

Posted 22 days ago

Job description

About the Role
This is the first dedicated data hire on Together AI's Finance team. You will own the data layer that Finance runs on - building from scratch the models, pipelines, and reporting infrastructure that allow Strategic Finance, FP&A, and Accounting teams to get reliable answers quickly. The person in this role will have direct exposure to every part of the Finance organization and a real opportunity to shape how data-driven decision-making develops here as the company scales.
A significant portion of your work will touch the data behind the economics of Together's infrastructure, which sits behind nearly every financial question we ask. You will work closely with Together's Data and Commerce engineering team, which owns the underlying billing pipelines and data warehouse. Your job is to define and build the modeling and reporting layer that turns raw operational data into finance-grade datasets - aligning on data contracts, representing Finance's requirements in data design decisions, and ensuring the metrics Finance depends on are correct, documented, and trusted.
Responsibilities
  • Own and evolve the dbt transformation layer for Finance: design, build, test, document, and maintain models covering billing, financial performance, compute unit economics, and operational metrics
  • Author and maintain Airflow DAGs (Astronomer-managed) that orchestrate Finance dbt runs, data quality checks, and downstream dependencies reliably
  • Deliver dashboards and reporting in Hex for the executive team covering financial performance, utilization, and key operating metrics
  • Partner with Strategic Finance, FP&A, and Accounting teams on the data infrastructure behind forecasting, cost modeling, and other financial analyses
  • Set data quality standards across Finance data products and own incident response when Finance-critical pipelines break
  • Build the data foundation - clean, well-structured, documented, and reliably maintained - that enables Finance team to self-serve data analysis and supports AI automation and agentic workflows
Requirements
  • 5+ years in an analytics engineering or data engineering role, with meaningful time supporting Finance or business operations teams
  • Expert SQL and production-grade dbt experience - models, tests, docs, snapshots, incremental strategies; you've designed a dbt project from scratch and maintained it
  • Hands-on experience with Snowflake and Airflow in production; familiarity with Astronomer and the Cosmos dbt integration is a strong plus
  • Solid dimensional modeling fundamentals: star schemas, slowly changing dimensions, fact table grain - you can apply Kimball principles without needing to look them up
  • Strong dashboarding skills with a track record of executive-facing reporting that people actually use; experience with Hex or a comparable notebook/BI tool
  • Clear communicator who can align stakeholders on metric definitions and translate between engineering tradeoffs and Finance requirements in both directions
  • High comfort with ambiguity; this role will require scoping problems from scratch, not executing against pre-defined specs
Nice to Have
  • Experience with financial data or billing data such as ARR, usage-based billing, invoice reconciliation, revenue recognition patterns, etc.. We operate a usage-based billing system and this context transfers directly.
  • Experience with PII handling, data masking, access-tier modeling, or compliance work (SOC 2, ISO 27001, GDPR, CCPA).
  • Familiarity with lakehouse patterns (Iceberg, Delta, Hudi) and hybrid warehouse/lake architectures.
  • Python for data tooling: automation, data quality frameworks, custom dbt macros or operators.
  • Experience with Hex, Metabase, or similar notebook/BI tooling that sits on top of your dbt models.
  • Prior experience in a high-growth AI/ML infrastructure or platform company
About Together AI
Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.
Compensation
We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200k -$240k + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.
Equal Opportunity
Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.
Please see our privacy policy at https://www.together.ai/privacy.

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