Data Scientist, Privacy

Key Skills

Apache Kafka, Machine learning techniques, Data science techniques, Apache Cassandra, Deep Learning, REDIS, Elasticsearch, Data Modelling, SPARK Programming, HBase, Apache Flink

Job Description

We are looking for data scientist candidates with strong data analytics background and solid software development skills, who can utilize data-driven techniques in building solutions to help measure, identify, and envision Bytedance's privacy evolution. You will help scope out projects, building operationalized analytics tools and platforms, and most importantly, use data to find insights, diagnose problems and tell compelling stories. From a privacy XFN view, you will work closely with various XFN teams including but not limited to legal, audit, PR/GR, and product. You will have opportunities to gain domain knowledge from your day by day work and gradually become a domain expert in privacy. From a technical perspective, you will have opportunities to learn and apply cutting-edge AI technologies to solve real-ward system operational challenges in live enterprise environment. You will take ownership for end-to-end application of ML/DL techniques, tracking its performance and iterate over time, and will sharpen your skills for robust software implementation and cross-team collaboration.

• Use data to identify trends, conduct root cause analysis and suggest potential opportunities for privacy gaps and improvements.
• Develop metrics to evaluate risks of the privacy overall with granular breakdowns and the effectiveness of privacy programs.
• Conceptualize, develop and maintain dashboards for risk detection and monitoring.
• Devise data-driven strategies to proactively identify, detect, and mitigate risk to our users data privacy and protection.
• Collaborate with members of XFN teams (e.g., data engineers, domain experts) on the project’s goals.

Qualifications

Role Requirement:

• B.S. In CS/statistics/math or equivalent experience, M.S./Ph. D. a plus - 2+ years of experience in data science or quantitative analysis.
• Familiar with ML/DL modeling approaches - Able to troubleshoot and tune model performance issues
• Strong communication skills across technical and non-technical audiences and the ability to synthesize and communicate complex concepts and analyses in easy to understand ways.
• Experience with data modeling and statistical analysis techniques, including: hypothesis testing, model evaluation, and common regression and classification algorithms.

Preferred Requirement:

• Experience of working in Privacy domain at a tech company.
• Experience in deep learning, distributed computing (Hive/Hadoop), or social network analysis.
• Proven experience leading data-driven projects from definition to execution, from defining metrics to communicating actionable insights
• Familiar with large data processing/storage tools such as Kafka, Flink, Spark, ElasticSearch, Redis, Hbase, Cassandra, Druid etc
• Hands on experience handling terabyte size datasets, applying statistics and machine learning techniques and algorithms, using visualization tools to present data.