Translate business requirements into software architecture and design;
Lead data analytics and data science work for individual use cases;
Implement & automate data collection from Internet Apps for analytics of content curation, placement, selection, and recommenders, e.g. using device farm or other methods;
Participate in Agile ceremonies, schedule and hold periodic code reviews, track own scope of work and progress using relevant tools;
Work to be done in Unix/Linux environment using Golang and scripting languages, designing and developing production quality data-driven algorithms, workflows, and functions;
Provide documentation to any and all new code development or code changes that are made to the existing code base, and document existing reports;
Identify, resolve and support the retest of all defects discovered during testing;
Assist in the deployment of the system to production, including validation that deployment was successful;
Support production issues in a timely manner dependent upon severity.
Skills
Must have:
3-5 years of experience;
BS or MS in Data Analytics/ Computer Science/Math/Applied Math or equivalent;
Strong experience with AI/ML models and techniques, such as supervised machine learning, decision trees, and logistic regression will help solve a range of data science problems, hands-on working knowledge of 3rd party, open source tools, such as supervised machine learning, decision trees, and logistic regression will help solve a range of data science problems;
Foundation in statistics and math;
Programming skills;
Knowledge of Python, and (highly desired) C and/or Golang;
Experience with ingestion of big data in near real-time, and data processing/parsing/normalization.
Nice to have:
Experience working with mobile devices using APIs, OS, and embedded software;
Experience working with web servers, HTML/Java, and web applications;
Experience with publish/subscribe models (such as Kafka) of data sharing/exchange;
Experience working with data packets, understanding of TCP/IP and networking;
Knowledge of video, audio, and streaming technologies;
