Senior Data Scientist / Machine Learning Engineer - Ads

As a Senior Data Scientist / Machine Learning Engineer at Faire, your primary responsibilities will involve developing solutions related to ads targeting, retrieval, and prediction/ranking. You will be part of a newly established team focusing on Ads Delivery and Advertiser Optimization, where you'll solve complex challenges and contribute directly to product impact.

Candidates applying for the Senior Data Scientist / Machine Learning Engineer position at Faire should ideally have at least 4 years of industry experience leveraging machine learning to address real-world challenges. A strong background in programming, experience with deep learning, and the ability to work collaboratively in teams are essential qualifications.

Success in the Senior Data Scientist / Machine Learning Engineer role at Faire hinges on strong programming skills and deep understanding of search, personalization, and ads. Additionally, being a self-starter with the ability to devise team strategies and lead model development independently will set you apart as a key contributor.

In the Senior Data Scientist / Machine Learning Engineer role at Faire, you'll apply machine learning techniques to improve the functionality and effectiveness of product discovery and advertising solutions. Your work will lead to innovative technology development aimed at helping local brands compete effectively in the marketplace.

The Senior Data Scientist / Machine Learning Engineer role at Faire offers competitive compensation ranging from $177,500 to $244,000 annually, along with equity and a range of employee benefits. A hybrid work model provides flexibility, allowing employees to work remotely for up to 4 weeks each year.

When discussing your relevant project, highlight the problem you addressed, the machine learning techniques you employed, and the outcome. Focus on your contributions, the impact of the project, and any challenges you overcame during the process.

Explain that your approach involves thorough problem definition, data exploration, and selecting the right algorithms based on the project's requirements. Describe how you iteratively develop and validate models, ensuring optimal performance through continuous learning.

Discuss any projects where you’ve worked on ads targeting and optimization, describing the techniques you used such as A/B testing, optimization algorithms, and the metrics you analyzed to measure success.

If you’ve worked with a two-sided marketplace, share insights into how you balanced the needs and interests of both sides. Describe any models you developed to improve user engagement or experience for both sellers and buyers.

List the programming languages like Python and R that you are proficient in, as well as machine learning libraries and frameworks like TensorFlow or PyTorch. Give examples of how you’ve used these tools in past projects.

Highlight your practices for staying informed, such as following reputable journals, attending conferences, participating in workshops, and engaging in online courses that focus on emerging trends and technologies in machine learning.

Emphasize your commitment to giving and receiving constructive feedback, sharing ideas and insights freely, and actively participating in team discussions. Describe how you believe collaboration enhances project outcomes.

Discuss your systematic approach for identifying issues in the model, whether related to data quality, feature selection, or algorithm choice, followed by steps you would take to iterate and improve model performance.

Explain that data preprocessing is critical for model performance and that you prioritize techniques for data cleaning, handling missing values, normalization, and feature engineering to ensure a high-quality input for models.

Share your alignment with Faire's mission and your passion for empowering independent businesses through technology. Express your enthusiasm for the impact you could create in driving positive economic outcomes for local communities.