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Principal Data Science Engineer
EngineeringSubmit Resume here
While we have offices in Seattle and Las Vegas, we are seeking the best talent to join our team and will consider Remote/Telework options for candidates located anywhere in the US.
Drive the practice of data processing, analytics and machine learning through a dedicated team of data engineers, data scientists and machine learning engineers to propel Company transformation into a data insights driven organization. Work with peers in cloud engineering, devops engineering to drive data driven insights through the enterprise.
- Provide technical leadership and mentoring for staff members; conduct regular reviews of project work, identify development opportunities through training and conferences, and create opportunities for collaboration and peer review.
- Partner with Product Management and Analytics team to plan, resource, and manage the execution of the project portfolio; identify and implement architectural support to maximize productivity, reduce the cycle time of projects, and ensure sufficient auditability and monitoring. Identify and develop required technical competencies and practices to support the project pipeline.
- Review and critique use cases for completeness and alignment. Estimate required data science resource levels and timelines for use cases.
- Assess opportunities for evaluation of and partnership with external machine learning (ML) and artificial intelligence (AI) companies/platforms as they align with company needs and strategic direction. Lead partnerships with adopted platforms.
- Develop an industry view of analytics and design-driven problem solving. Use academic and competitor research to understand recent advances and best practices and inform our approach to developing solutions.
- Identify data engineering and science use-cases, help in architecting and developing data engineering framework and establish agile methodologies for data science use-cases.
- Masters degree in computer science, mathematics, statistics, physics, or related quantitative field
- Ten years of progressive experience in a data science or quantitative role, including two years leading a team of data engineers and scientists.
- Experience managing a portfolio of projects from inception to deployment
- Experience communicating with leadership at all levels
- Experience developing a range of statistical and machine learning models (e.g. natural language processing, computer vision, anomaly detection, forecasting, etc.)
- Business acumen to work with business partners and understand their domains, processes, and issues to identify strategies to optimize and innovate
- Ability to leverage data visualizations to highlight insights to business partners and make a business case for a recommended action or innovation opportunity
- Proficient in the language of statistics with an advanced understanding of mathematical statistics, including combinatorics, probability, common discrete and continuous distributions, univariate and multivariate distributions, conditional probability, random variables, expectation, variance, convergence, estimation (bias, MSE, consistency, sufficiency, maximum likelihood, moments, etc.), hypothesis testing, and confidence intervals. This understanding is required to assess and coach data scientist's work
- Theoretical and practical understanding of a range of machine learning techniques including unsupervised learning (e.g. clustering, outlier detection, PCA, ICA, NNMF, SVD, etc.), supervised learning (e.g., regression techniques, nave Bayes, support vector machines, LDA, decision trees, neural networks, etc.), reinforcement learning (e.g., Q-learning, neural networks, etc.), and meta-methods (e.g., boosting, bagging)
- Leadership skills to influence outcomes in partnership with data scientists, data engineers, product managers, business leaders, technology management, and other subject matter experts
- Written communication skills to engage partners, document methodology and results, and publish research
- Organizational and project management skills for overall project planning and task management
- Solid understanding of (1) multivariate calculus with applications to optimization, (2) linear algebra and tensor calculus, (3) partial differential equations, (4) graph theory, (5) numerical analysis.
- Solid understanding of (1) data structures, (2) sequential algorithms, (3) distributed algorithms, (4) complexity
- Knowledge of information technology integration and deployment patterns to design and implement solutions
- Advanced proficiency in one programming language like Java, Scala or Python.
- Advanced proficiency in data processing frameworks like Pandas.
- Advanced proficiency in TensorFlow, Keras, Cloud based ML frameworks, external ML libraries.
- Project and/or program management experience.
- Experience in representing company in International ML conferences.
- Proficiency in cloud and ML deployment strategies.
- Proficiency in exploring new avenues for data based insights for new workstream initiatives
- Flexible work hours and work from home options
- Accessible and transparent leadership team
- Paid time off every year to volunteer and generous parental leave
- Medical, dental, vision benefits, 401(k) plan with a company match
- Part of the WarnerMedia family of powerhouse brands
Who We Are
iStreamPlanet is one of the largest streaming platforms in the world for broadcasters; doing thousands of events a year such as March Madness, World Cup, and even the Olympics. You probably have not heard of us but we power some of the most well-known media brands in the world. Our mission is to provide a one-stop platform for the media industry as they convert from traditional broadcast to all online streaming over the next decade. We are backed by giants such as WarnerMedia (owners of Warner Brothers, HBO, Turner, etc.) and are at the heart of changing how you get your sports and entertainment in the future.
iStreamPlanet Co., LLC is an equal employment opportunity employer. iStreamPlanet does not discriminate against any applicant or employee based on race, color, religion, national origin, gender, age, sexual orientation, gender identity or expression, marital status, mental or physical disability, and genetic information, or any other basis protected by applicable law.