Data Scientist (Python, SQL/SparkSQL, Git, machine learning) | TELECOMMUTE | EISamprasoft • United States
Data Scientist (Python, SQL/SparkSQL, Git, machine learning) | TELECOMMUTE | EI
Samprasoft
- United States
- United States
À propos
Work location options: 100% telecommute Minneapolis onsite San Francisco onsite Hours: 9am-5pm weekdays, with flexibility occasionally required to accommodate timezone differences Interview process: 2 rounds via video 1 screening interview 1 multi-part interview with team members Description: The data scientist has education and professional experience in statistics and machine learning. They are experienced with Python and SQL, and have familiarity with Spark, R, and Git, and they will apply software-development best practices to their code, and help others apply them as well. Familiarity with Databricks and/or Ascend, medical claims data, Agile methodologies, and cutting-edge use of LLM’s are each preferred as well. This data scientist conducts the entire lifecycle of machine learning projects, including creating proposals, determining requirements, defining model targets, creating and evaluating candidate models, and productionizing models and the pipelines they depend upon. They also can capably mentor junior members of the team, conduct large-scale exploratory or experimental analytical projects, and propose and prototype novel applications of Data Science to business problems. Team: Data Science team is composed of 5 full-time data scientists with a range of levels of background experience, and we will have as many as 3 full-time interns during the summer months. The team’s work areas tend to be separate from one-another; a Senior Data Scientist should see it as an exciting challenge to gain some level of understanding in each of them and be able to contribute to as many as possible. Responsibilities: Work with stakeholders and others on the present project to ensure that value is being delivered at a regular pace Work with SME’s to understand even the most nuanced context behind what is recorded in our data Work with technical partners (e.g., Data Engineers) to ensure that assets developed for analytical/modeling purposes are stable, reliable, and reproducible Write readable, maintainable, and testable code to ensure that datasets and models trained on them are delivering the expected results Read and contribute to others’ code to help it meet the same standards Mentor junior members of the team in fundamentals of delivering value through Data Science Propose new applications of Data Science to business problems, or help develop these proposals Ideal background: This candidate has a solid foundation of education in AI/ML, and experience applying this education to business problems. They can spot opportunities to deliver value, even in legally-regulated contexts, and follow through to make sure that their ideas don’t get lost along the way. They have high standards for their own work, and they are happy to contribute to guide others’ work to help them meet the same standard, when requested. This candidate is driven to meet objectives and is not going to simply give up when faced with a dependency they don’t know how to pursue. But they are also willing to accept reality, and when something they have been working on is not living up to expectations they will honestly consider whether it is worth continuing to invest time in that project. Required: Python for data-related applications (pandas, numpy, pyspark, etc.
Compétences linguistiques
- English
Avis aux utilisateurs
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