Applied Scientist, Recommendation, E-Commerce Alliance

Applied Scientist, Recommendation, E-Commerce Alliance

Location:

San Jose

Employment Type:

Regular

Job Code: A75536

• Collaborate with cross-functional teams to design, develop, and deploy sophisticated machine learning algorithms to enhance the performance of our recommendation systems.
• Utilize ML, NLP, and CV techniques to handle real-world signals generated from products, creators, merchants, e-commerce transactions, and so on.
• Design and deploy the large recommendation model in an online learning manner to serve billions of queries and products.
• Formulate end-to-end machine learning models for recommendation systems, ensuring their efficient and effective operation.
• Analyze extensive, complex datasets to extract meaningful insights, identify opportunities for improvement, and facilitate data-driven decision‑making.
• Design and execute experiments, testing and iterating on machine learning models to optimize recommendation functions and boost user satisfaction.
• Stay abreast of the latest advances in machine learning and recommendation systems, integrating this knowledge into your work.
• Clearly communicate complex technical concepts, methodologies, and results to a diverse audience, influencing decisions based on your findings.
• Adhere to stringent data governance and privacy protocols, ensuring all user data is handled responsibly and ethically.

• PhD or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative discipline.
• Solid experience in machine learning, deep learning, data mining, or artificial intelligence.
• Proficient in programming languages such as Python, C++, Java, or similar.
• Deep understanding of recommendation algorithms and personalization systems.
• Excellent problem‑solving and analytical skills.
• Strong ability to communicate complex ideas effectively to both technical and non‑technical audiences.

• Experience with reinforcement learning techniques.
• Proven modeling/algorithm competition records on Kaggle or top conferences’ challenges.
• Proven programming competition records on ICPC, IOI or USACO.
• Experience working with recommendation systems, computational advertising, search engine, or e‑commerce recommendation systems.
• Publications in machine learning or related conferences or journals are highly desirable.

The base salary range for this position in the selected city is $150,000 - $316,800 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

The company is an equal opportunity employer. Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Criminal history may impact certain job duties, potentially resulting in the withdrawal of a conditional offer of employment.