STEMBoard is seeking a Data Scientist with knowledge in programming for integrating complex models and using advanced software library frameworks to distribute large, clustered data sets. The data scientist work with a team of data scientists and engineers that collect and arrange data in a form that is useful for analytics. A knowledge of machine learning is also desired to build efficient and accurate data pipelines to meet the needs for downstream users such as data scientists to create the models and analytics that produce insight.

Responsibilities:

A data scientist will have skills sets of both data analysts and data engineers. Data scientists are responsible for designing, implementing, and maintaining a data pipeline. In addition, data scientists shall interpret and analyze complex sets of data, as well as plan, execute, and manage ML projects with cloud-native platforms and advanced ML solutions. They understand some of the most challenging processes, technologies, and can leverage a vast array of methodologies in the field, such as data mining, natural language programming, and machine learning.

Data scientists must have a combination of skills that includes programming, mathematical modeling, statistics, and domain knowledge. They must combine an advanced math and statistics background with programming, domain knowledge, and communication skills to analyze data, create applied mathematical models, and present results in a form useful to the organization. They must also be able to understand and manipulate structured and unstructured large data sets, which requires proficiency in distributed SQL programming, relational and non-relational data queries, general programming languages (such as Python and R,) and machine learning techniques.

• Apply and develop scientific methodology, statistics, and algorithms to discover and frame relevant problems, hypotheses, and opportunities.
• Develop predictive and prescriptive modeling, natural language processing (NLP), Robotic Process Automation (RPA), text mining and processing, clustering, forecasting methods, and other advanced statistical techniques.
• Design and automate processes to facilitate the manipulation and analysis of data. Manage and integrate data across dissimilar data sets. Analyze large-scale structured and unstructured data.
• Use frameworks such as Spark and Hadoop to conduct large-scale data processing. Perform statistical modeling and create data visualizations using products like Tableau, Microsoft Power BI and R Shiny.
• Research, design, and implement algorithms to solve complex problems. Program using R, Python (NumPy, SciPy, Pandas) or similar analytical languages.
• Perform data engineering, data processing and modeling techniques using cloud-based data management, data science, and ML platforms such as Databricks, IBM Cloud Pak, Cloudera, and Snowflake.
• Communicate complex concepts and hypothesis to a non-technical audience through digital storytelling.
• plements cloud agnostic data toolsets, Mentors' data science teams on best data practices, Implements OCI complaint containers, AI/ML pipelines, related storage solutions, and infrastructure as code.

Requirements:

• Experience: 1+ years of experience with software engineering, data science or related experience.
• Education: Bachelors or degree in STEM with a preference towards Data Science, Computer Science, or Software Engineering.
• Tools: Proficient with one or more programming languages (Java, C++, Python, R, etc.)
• Security Clearance: minimum of SECRET level
• Proficient in Agile Development and Git Operations.
• Demonstrated experience applying data science methods to real-world data problems.

Benefits:

• Healthcare, Vision, and Dental Insurance
• 20 Days of PTO
• Wellness Hours
• 401K Matching
• Training/Certification Reimbursement
• Short term/Long term disability
• Parental/Maternity Leave
• Military Leave
• Life Insurance