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Backtesting Jobs in Oregon (NOW HIRING)

OR

$300K - $537K/yr

... backtesting, deployment, and monitoring - and lift the accuracy and reliability of existing forecasts Partner with Finance & Strategy and Product leadership to translate forecast outputs - including ...

OR

$300K - $537K/yr

Contribute to and advance the team's forecasting pipeline - model development, backtesting, deployment, and monitoring - and lift the accuracy and reliability of existing forecasts * Partner with ...

Partner with other members of the Product & Technology team to validate valuation models through rigorous backtesting and experimentation * Collaborate with domain experts to improve feature ...

Backtesting information

What are the key skills and qualifications needed to thrive as a Backtesting Analyst, and why are they important?

To thrive as a Backtesting Analyst, you need a strong background in quantitative analysis, statistics, programming (typically in Python or R), and familiarity with financial markets, usually supported by a degree in mathematics, finance, or a related field. Proficiency with backtesting platforms (such as QuantConnect or Zipline), data analysis tools, and version control systems like Git is often required. Attention to detail, critical thinking, and strong problem-solving abilities are key soft skills that help ensure robust model evaluation and development. These skills are vital for accurately assessing trading strategies and minimizing risk in real-world financial applications.

What is backtesting?

Backtesting is the process of evaluating a trading strategy or investment model by applying it to historical market data. This helps traders and analysts see how the strategy would have performed in the past, which can provide insights into its potential effectiveness and risks. While backtesting can help identify strengths and weaknesses, it's important to remember that past performance is not always indicative of future results. The reliability of backtesting depends on data quality, strategy design, and how well it simulates real trading conditions.

What are some common challenges faced when backtesting trading strategies, and how can they be managed?

One common challenge in backtesting trading strategies is the risk of overfitting, where a model performs exceptionally well on historical data but fails in live markets. Data quality and availability can also pose issues, as incomplete or inaccurate data may skew results. To manage these challenges, it's important to use out-of-sample testing, robust data cleaning processes, and to validate strategies on multiple datasets. Collaborating with quantitative analysts and developers can also help ensure the backtesting process is thorough and reliable.

What is the difference between Backtesting vs Quantitative Analyst?

AspectBacktestingQuantitative Analyst
Primary RoleTesting trading strategies using historical dataDeveloping and implementing quantitative models for investment decisions
Required SkillsData analysis, programming, finance knowledgeMathematics, programming, financial theory
Work EnvironmentTrading firms, hedge funds, financial institutionsAsset management firms, hedge funds, banks
CertificationsOften none required, but CFA or CQF helpfulCFA, CQF, or advanced degrees common

Backtesting focuses on evaluating trading strategies with historical data, while a Quantitative Analyst develops models to inform investment decisions. Both roles require strong analytical skills and finance knowledge but differ in scope and responsibilities.

What are popular job titles related to Backtesting jobs in Oregon? For Backtesting jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Backtesting jobs in Oregon look for? The top searched job categories for Backtesting jobs in Oregon are:
What cities in Oregon are hiring for Backtesting jobs? Cities in Oregon with the most Backtesting job openings:
Machine Learning Scientist 4 - Subscription Forecasting

Machine Learning Scientist 4 - Subscription Forecasting

Netflix

OR

$300K - $537K/yr

Other

Medical, Life, Retirement, PTO

Posted 2 hours ago


Netflix rating

5.8

Company rating: 5.8 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

57th of 65 rated media


Job description

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology.

Come be a part of what's next. The Team Netflix's ability to invest in the content that entertains hundreds of millions of members - billions of dollars each year across film, series, games, and live experiences - depends on getting subscription pricing right and having a clear view of where the business is headed. The Subscription Revenue DSE team brings measurement and modeling to both challenges.

We are a small, focused group of data practitioners who work across pricing research and business forecasting. This role will focus on the forecasting work, where we partner with Finance & Strategy, Content, and Revenue Analytics teams to build the models that project Netflix's subscriber growth, engagement, and revenue across global markets over multi-year horizons. Our forecasts serve as a foundation for long-range planning across the company.

The Role You will work closely with senior researchers and the team's existing data science foundation to improve the models that forecast Netflix's subscription trajectory and the expected impact of pricing decisions. The core challenge: subscription markets are noisy, global, and deeply interconnected. Understanding how the business will develop - and how pricing actions will shift that trajectory - across geographies, plan tiers, and time horizons requires strong models and honest judgment about what the data can and can't tell you.

What You Will Do Build and productionize forecasting models that capture the overall trajectory of Netflix's subscription business alongside the expected impact of pricing actions on member base, ARPU, and revenue across global markets Build on the team's existing scenario modeling and simulation tools to quantify how pricing actions and broader market dynamics are expected to affect subscription metrics - giving decision-makers a way to stress-test assumptions before a pricing move happens Contribute to and advance the team's forecasting pipeline - model development, backtesting, deployment, and monitoring - and lift the accuracy and reliability of existing forecasts Partner with Finance & Strategy and Product leadership to translate forecast outputs - including their uncertainty - into concrete business recommendations About You Solid grasp of subscription business dynamics - how acquisition, ARPU, and churn interact, and how pricing decisions move these metrics Strong expertise across forecasting methods - such as time series, and regression-based approaches - and the trade-offs between accuracy, interpretability, and stability Comfortable building production forecasting systems: backtesting, monitoring, catching drift, and retraining when the data changes You incorporate macro and external signals (economic conditions, FX dynamics, competitive moves) into your models alongside internal data Proficient in Python and SQL, with hands-on experience with ML and statistical libraries (e.g., statsmodels, PyTorch) Advanced degree (MS or PhD) in statistics, economics, computer science, or a related quantitative field, or equivalent applied experience Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range

The range for this role is $300,000.00 - $537,000.00. This compensation range will vary based on location. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits

We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off.

See more details about our Benefits here. Netflix is a unique culture and environment. Learn more here.

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams.

We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. Job is open for no less than 7 days and will be removed when the position is filled.


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About Netflix

Sourced by ZipRecruiter

Netflix is the world's leading streaming entertainment service with 222 million paid memberships in over 190 countries enjoying TV series, documentaries, feature films and mobile games across a wide variety of genres and languages. Members can watch as much as they want, anytime, anywhere, on any Internet-connected screen. Members can play, pause and resume watching, all without commercials or commitments.

Industry

Arts, entertainment, and recreation

Company size

5,001 - 10,000 Employees

Headquarters location

Los Gatos, CA, US

Year founded

1997