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Simply stated, this executive leadership position will be responsible for and resourced to create a vision of how data science can continue to transform our organization.
HBM businesses develop and market data used every day for critical functions in healthcare, transportation, and finance. At our core we leverage data and expertise to answer critical questions that come up as people do their jobs, from selecting the right drug for a patient to estimating a repair for a car. We have an extraordinary diversity of data, across industries and applications therein. Plus, we re growing both organically and by acquisition (which means even more data sets!).
As successful as we are, our aspiration is to do even better. Data it at the heart of what we do but we think we can improve. We ve seen the amazing feats achieved by modern AI technology and believe we are at the beginning of a period of unprecedented innovation. We re starting an ambitious project to assist our businesses with building their products and developing new ones. This work will require handling transactional data, manufacturing information, and human-curated content. We ll leverage ML, deep learning, semantic modeling, probabilistic programming, and likely pioneer some new techniques. If the idea of this much diversity, of industry, of technique, of content, excites you then we want to speak to you!
This is a hands-on role. Although you will be leading a small team, we fully expect your hands will be on keyboard often. Right now, the project is in its initial phase: the first few members of the team have been recruited, the lab space has been built out, the individual projects along our journey need to be selected and defined. We have resources, executive sponsorship at the highest levels of the company, and a multi-year commitment. What we need is an entrepreneurial leader who is passionate about modern analytical capabilities/techniques and is at home working to define, build, and (of course) execute this program.
Combine top analytical skills with knowledge of our businesses to build and produce models to impact our business in positive ways.
Work with other data scientists with a broad range of analytical expertise and subject matter experts to deliver data products and provide business insights through quantitative analysis (Predictive Modeling, Optimization, Visualization, etc.)
Assist in the testing and implementation of the models and analysis created
Extract data from various applications and systems, in particular large relational databases, manipulate, explore data and build models using quantitative, statistical and visualization tools.
Mentor and manage Data Scientists and Engineers
Present findings, both formally and informally, to audiences at all levels of the organization
Serve as an internal expert consultant to senior leadership of Hearst Business Media
In collaboration with the product management, content development, and engineering teams, identify opportunities to leverage data science techniques in order to create new or improve existing products
Evangelize the use and potential of data science within the organization and in particular the executive, product management and engineering teams
Engage with academic community and peer organizations to maintain a current view of technical capabilities and best practices
10+ years of experience in relevant areas of computer science, including applied machine learning, deep learning, NLP or related disciplines
Strong statistical background and experience implementing systems in production
Strong foundation in coding skills relevant to data science, e.g., Pig, Hive, SQL, Python, etc.
Extensive experience solving analytical problems using quantitative approaches
Experience developing production-quality data products using the results of quantitative research
Track record of successfully managing a diverse team of highly skilled individuals.
Must be able to communicate effectively with (non-technical) senior executives internally and externally. Presentation skills are essential.
Familiarity with modern data pipelines and ETL practices
Doctorate degree in a quantitative field (e.g., computer science, physics, engineering, mathematics, etc.)
Experience in one or more of: Transportation, Healthcare, or Finance
Experience with open source machine learning platforms
Experience with cloud-based data processing environments
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