Úta Scientist

Overview At SolarWinds, we’re a people-first company. Our purpose is to enrich the lives of the people we serve—including our employees, customers, shareholders, Partners, and communities. Join us in our mission to help customers accelerate business transformation with simple, powerful, and secure solutions. The ideal candidate thrives in an innovative, fast-paced environment and is collaborative, accountable, ready, and empathetic. We’re looking for individuals who believe they can accomplish more as a team and create lasting growth for themselves and others. We hire based on attitude, competency, and commitment. Solarians are ready to advance our world-class solutions in a fast-paced environment and accept the challenge to lead with purpose. If you’re looking to build your career with an exceptional team, you’ve come to the right place. Join SolarWinds and grow with us! Your Role: As a member of the Business Data Science team, you will be able to influence business decisions and processes through business insights, statistical modeling, machine learning and other advanced analytical approaches. The Data Scientist will drive analysis by collaborating with members of the business, identifying analysis opportunities, creating requirements, consistently meeting and updating stakeholders, performing analysis through a variety of business intelligence and data science methodologies, and delivering results to all audiences from executives to engineer. The ideal candidate is strongly suited to work independently, research and remain updated on data science methodologies, lead and collaborate with stakeholders to gain full understanding of the business problem and comfortable presenting analysis. Responsibilities Complete full life cycle of data science projects from identifying analysis and creating a reproducible environment to training and implementing a model to deliver actionable business results Conduct thorough analysis to gain deep understanding of data and identify key trends and conclusions. Focus on overall business and organizational operations to create actionable and interpretable analysis. Apply advanced statistical modeling to business outcome, including regression, time series, longitudinal analysis, categorical analysis, survival analysis, clustering and segmentation, neural networks, deep learning, and natural language processing (R or Python). Monitor deployed models over time through statistical evaluation and assess businesses effectiveness through applied model results. Operate within a data science environment and team process. Collaborate with data science, business intelligence, developers, engineers, data governance and other functional areas of the business. Communicate across multiple channels to get access to data, identify key data features, and work with developers to build data structures. Excellent ability to answer questions through data with minimal guidance Effectively communicates data science projects and results into simple, easily understood, and actionable takeaways to key stakeholders. Regularly meet with project consumers to evaluate results. Build relationships with stakeholders to create new analysis opportunities. Communicate with stakeholders, identify business requirements, manage project roadmap, execute on project tasks while concurrently working on more than one projects. Qualifications 3+ years working in a collaborative Data Science or Business Intelligence environment. Intermediate to advanced skill in one or several of the following selected technologies: R, Python, SAS, SQL or similar language. Azure experience a plus. Ability to create, work within, share, and scale data science environments (Linux, PowerShell, environment, docker, version control, git, python, jupyter, Rstudio, vscode, and other similar processes) Passion for analytics, driving to results and intellectual curiosity. Desire to help drive immediate improvement in business results. Understanding and knowledge in data science methodologies including regression, time series, longitudinal analysis, categorical analysis, survival analysis, clustering and segmentation, neural networks, deep learning, and natural language processing. Experience implementing a broad range of data science methodologies, understanding of the statistical concepts as well as the implications behind the methodologies to avoid common pitfalls. Experience creating interactive visualization dashboards for a broad audience (Python, R, Tableau). Excellent communication skills, ability to translate results across multiple business platforms into simple, easily understood results. Natural ability to effectively communicate results to a technical and non-technical audiences. Exceptional project and organizational and time management skills, able to prioritize multiple complex assignments. Ability to quickly identify and solve problems in a fast paced, changing environment. Bachelor’s degree in relevant field (statistics, data science, computer science, operations research). Post graduate degree in statistics, mathematics, or related field a plus.