Machine Learning Engineer (Data Mining) - TikTok Shop

TIKTOK PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

TikTok is seeking a data-focused engineer/scientist to join our e-commerce data team in building data-driven capabilities for insights, tagging, and productization. You will collaborate with PMs to optimize data products using large-scale data across user, traffic and commerce signals.

Strong background in ML, data mining, and big data processing is required, with experience in TensorFlow/PyTorch and Hadoop/Spark ecosystems. This role focuses on scalable data solutions for e-commerce growth.

Qualifications

• B. Sc or higher degree in Computer Science or related fields.
• 5 years experience in data structures and algorithms, familiar with machine learning, NLP, and data mining.
• Proficiency in Python/Java/Go/C++ and familiarity with data processing technologies (Hadoop, Spark, Hive, Storm, Flink).
• Familiar with data mining techniques and ML algorithms (GBDT, Xgboost, FM, DFM) and their principles.
• Proficiency in data mining tools and ML frameworks (TensorFlow, PyTorch).

Responsibilities

• Develop data-empowered capabilities for the e-commerce platform to extract and apply key insights from large data volumes.
• Perform data mining, build tagging systems, analyze user, traffic and commerce data to improve GMV.
• Analyze data-related business problems and translate into data requirements for implementation.

Skills

Data structures

Algorithms

Machine learning

Natural language processing

Data mining

Data analysis

Education

Bachelor's degree in Computer Science or related field

Tools

Python

Java

Go

C++

Hadoop

Spark

Hive

Storm

Flink

TensorFlow

PyTorch

Job description

About TikTok

TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us

Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.

We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an \"Always Day 1\" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.

Diversity & Inclusion

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.

Responsibilities

About The Team

The e-Commerce industry has seen tremendous growth in recent years and has become a hotly contested space amongst leading Internet companies, and its future growth cannot be underestimated.

With millions of loyal users globally, we believe TikTok is an ideal platform to deliver a brand new and better e-commerce experience to our users. Our product engineering team is responsible for building an e-commerce ecosystem that is innovative, secure and intuitive for our users. We are looking for passionate and talented people to join us as we drive the future of e-commerce here at TikTok.

Responsibilities

• Responsible for development of data-empowered capabilities for e-commerce platform, enable different e-commerce verticals to extract and apply key insights from oceans of data to meet their business needs.
• Data mining for e-commerce, building tagging system based on massive data, analysing user, traffic, e-commerce and other data, combining with business to improve GMV.
• Data analysis, mining, model specific productization; understanding of e-commerce business, able to work with PM to continuously optimize data products based on data-driven.
• Develop data mining pipelines to extract data assets (eg. entity labels) from aggregated data and enable the extraction of actionable insights from large volumes of domain data.
• Design and development of various strategies, algorithms and machine learning techniques to improve the accuracy and coverage of extracted data assets.
• Analyze e-commerce data-related business problems and abstract them into data-related requirements that are then implemented to help resolve key business problems.

Qualifications

Minimum Qualifications

• B. Sc or higher degree in Computer Science or related fields from accredited and reputable institutions.
• 5 years experience in data structures and algorithms, familiar with one or more: machine learning, natural language processing, data mining.
• Familiar with one of the Python/Java/Go/C++ programming languages.
• Familiar with common data processing technologies (Hadoop, Spark, Hive, Storm, Flink), with demonstrable coding skills.
• Familiar with common data mining techniques and machine learning algorithms (GBDT, Xgboost, FM, DFM, etc.), and familiar with their principles and scope of application.
• Proficiency in data mining, machine learning tools and common frameworks (TensorFlow, Pytorch).

Preferred Qualifications

• Continuous learning, keeping up with the latest research directions and results in the field of machine learning, for the exploration of big data applications in various vertical areas.
• In-depth research experience in analysis and mining of user behaviour data and construction of user portraits.
• Data mining experience in vertical industries (e-commerce, finance, games, travel, real estate, etc.).
• Development and optimisation of advertising and recommendation algorithms.