Machine Learning Engineer - Marketplace Growth (TikTok Global E-commerce Supply Chain and Logistics)

Role Summary

We are seeking a talented and motivated Machine Learning Engineer with expertise in marketplace growth to join our dynamic and fast-paced team. In this role, you will collaborate with cross-functional teams including data scientists, engineers, product managers, and business stakeholders to develop innovative solutions that unlock the value hidden within our data, leading to improved decision-making and operational efficiencies.

Responsibilities

About the team!

The E-Commerce Supply Chain and Logistics team is dedicated to enhancing clients' shopping experience and reducing operational costs in the supply chain and logistics of TikTok E-commerce by developing end-to-end algorithm capabilities using machine learning, operations research, data mining, and causal inference methods.

1. Design and develop machine learning algorithms for various tasks, including but not limited to customer segmentation, scoring, outreach, marketing, characterization, and incentive optimization.
2. Support marketplace growth business goal attainment through optimizing outreach based on click through rate estimation, outreach timing selection, target audience selection and causal studies.
3. Collaborate with data scientists, analysts, and subject matter experts to define data mining objectives and develop strategies to address complex business problems and opportunities.
4. Apply feature engineering techniques to derive relevant features and embeddings from raw data and improve the performance of data mining models.
5. Evaluate and benchmark different machine learning approaches, algorithms, and tools, and recommend the most appropriate solutions based on performance, scalability, and interpretability.
6. Stay updated with the latest advancements in data mining, machine learning, and related fields, and apply this knowledge to enhance the team's capabilities and identify new opportunities.
7. Communicate findings, insights, and technical concepts effectively to both technical and non-technical stakeholders, fostering a collaborative and data-driven decision-making culture.

Requirements

1. Master's or advanced degree in Computer Science, Data Science, Statistics, or a related field.
2. 3+ years experience as a Machine Learning Engineer, Data Scientist, and experience in Deep Learning is preferred
3. Work experience in user growth, marketing algorithms, recommendation algorithms, advertisement algorithms or related fields is preferred.
4. Proficient in using SQL + Python and experience with data manipulation and analysis libraries, experience with TensorFlow or PyTorch is preferred.
5. Experience with big data processing frameworks (e.g., Hadoop, Spark) and distributed computing for efficient data mining on large-scale datasets.
6. Solid understanding of machine/deep learning concepts and techniques, including feature engineering, model evaluation, and optimization.
7. Strong analytical and problem-solving skills, with a demonstrated ability to handle and derive insights from complex and unstructured datasets.

Preferred Qualifications

1. Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and convey technical concepts to non-technical stakeholders.
2. Publications at KDD, NeurIPS, WWW, SIGIR, WSDM, CIKM, ICLR, ICML, IJCAI, AAAI and related conferences.

Job Information

[For Pay Transparency] Compensation Description (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.

Benefits may vary depending on the nature of employment and the country work location. 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.

About the Company

The Global Business Solutions (GBS) team is responsible for the revenue growth of the TikTok business, and our teams include Sales, Marketing, Ops, Account Managers, Agency and partnerships, as well as Marketing Science.

At TikTok, our Global Business Solutions (GBS) team plays a key role in generating revenue by promoting our advertising solutions, onboarding new clients, driving ad campaigns, and more. As the TikTok community grows at an unprecedented speed around the world, our GBS team leads groundbreaking projects that are changing the landscape of the advertising industry in real time.

We're seeking an analytically driven, and detail-oriented Client Solutions Manager (CSM) Intern to join our Ecommerce Team. As a CSM, you will partner closely with Client Partners and Client Solutions Managers to drive revenue by identifying opportunities, leveraging data insights, and delivering consultative solutions for advertisers.

This role centers on client education, relationship growth, data analysis, and campaign success. You will provide strategic recommendations to both clients and internal teams, ensuring campaigns achieve business objectives while optimizing long-term partnerships. Success in this role requires strong data analytics skills, adaptability in a fast-paced environment, and a test-and-learn mindset to uncover the best solutions.

Additional Information

For Los Angeles County (unincorporated) Candidates

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. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
3. Exercising sound judgment.