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

Join us.

Data-E-commerce-Global Supply Chain and Logistics team:
Our 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.

Role Overview:
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:
1. Utilize advanced machine learning techniques to analyze large-scale datasets and identify meaningful patterns, correlations, and trends related to TikTok's global e-commerce supply chain and logistics operations.
2. Design and develop machine learning algorithms for various tasks, including but not limited to customer segmentation, marketing, user characterization, and predictive modeling.
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. Develop scalable and efficient data pipelines to preprocess and transform data for machine learning tasks, ensuring data quality, consistency, and availability.
6. Evaluate and benchmark different machine learning approaches, algorithms, and tools, and recommend the most appropriate solutions based on performance, scalability, and interpretability.
7. 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.
8. Communicate findings, insights, and technical concepts effectively to both technical and non-technical stakeholders, fostering a collaborative and data-driven decision-making culture.

Qualifications

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.
8. Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and convey technical concepts to non-technical stakeholders.
9. Publications at KDD, NeurIPS, WWW, SIGIR, WSDM, CIKM, ICLR, ICML, IJCAI, AAAI and related conferences.
TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at dataecommerce.accommodations@tiktok.com.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $129200 - $194750 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.

Our company benefits are designed to convey company culture and values, to create an efficient and inspiring work environment, and to support our employees to give their best in both work and life. We offer the following benefits to eligible employees:

We cover 100% premium coverage for employee medical insurance, approximately 75% premium coverage for dependents and offer a Health Savings Account(HSA) with a company match. As well as Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life and AD&D insurance plans. In addition to Flexible Spending Account(FSA) Options like Health Care, Limited Purpose and Dependent Care.

Our time off and leave plans are: 10 paid holidays per year plus 17 days of Paid Personal Time Off (PPTO) (prorated upon hire and increased by tenure) and 10 paid sick days per year as well as 12 weeks of paid Parental leave and 8 weeks of paid Supplemental Disability.

We also provide generous benefits like mental and emotional health benefits through our EAP and Lyra. A 401K company match, gym and cellphone service reimbursements. The Company reserves the right to modify or change these benefits programs at any time, with or without notice.