With a deep understanding of ML frameworks, ML pipelines and statistics you'll leverage your programming, data wrangling, and analytical expertise to solve business problems, build data products and frameworks, track performance, automate testing, and more. Working closely with the rest of our Analytics team and partnering with our BI team, you'll assist in creating the foundation for how we build data-driven applications, tools, and experiences for our internal business partners.
What you'll be doing?
- Execute the data vision strategy and goals ensuring those are consistent with the Division's business requirements.
- As part of the Data Science team, help develop analytical capabilities, data products and tools to enable data query and deliver solutions to business requests
- Contribute and provide thought leadership to the business and key stakeholders.
- Develop new approaches to understand the consumer and solve complex business problems such as optimizing product performance, gross profit and adoption.
- Generate actionable audience insights using advanced statistical techniques such as predictive statistical models, audience profiling, segmentation analysis, survey and test design, exploratory analysis and data mining.
- Understand in depth, design and inform statistical testing for audience strategy
- Design user interfaces to overlay ML models, and enable business partners to access models, query results and scenarios.
- Build presentations and reports to communicate statistical modeling results
- Can manage ingestion and cleansing of large unstructured data and developing analytical capability to query the data and respond to user requests using a wide range of technologies including.
- Productionalize codes and models via various tools and technologies (such as R Connect and R Studio) to deliver scale, efficiency and speed.
- Profile, explore, connect and analyze extensive, often disjointed, and unstructured datasets including product meta data, user level data, primary research, audience profiles, social commentary and DMP data.
- Must have an in-depth knowledge of advanced statistical techniques, machine learning, feature engineering, and model evaluation techniques including regressions, cluster analysis test design, variable reduction, non-parametric tests and forecasting methodologies.
- Experience with A/B testing and test designs
- Experience with big data, standardizing and appending variables across disparate data sets
- Experience analyzing user level data (PII and anonymized), DMP data, social data and viewing / transactional or streaming data.
- 3-4 years' experience developing production ML models to solve problems such as product recommendations, audience classification, path modelling, look-a-like modelling and performance optimization
- BA/BS degree required with technical focus (e.g. mathematics, computer science, physics)
- MS or PhD degree preferred (but not essential)
- Ability to work with data and platform engineers to implement ML pipelines
- Experience with R and SQL and preferably a scripting language (Perl, Python)
- Business experience in media industry preferred, but not required
- Results oriented, excel in organizational skills, have strong attention to details and be able to effectively manage multiple projects/assignments simultaneously.
- Curious about data and problem solving: intrinsic ability to look at data and identify patterns, problems, or analysis opportunities
- Strong communication skills and the ability to explain complex analyses to both technical and non-technical audiences
- Effective data visualization skills with analytical tools such as Tableau, Shiny
- Collaborative – a team player who can thrive as an individual but also enjoy providing mentorship, learning, and being collaborative in cross-functional teams