Senior Data Scientist

Nelnet•Remote - Nebraska, NE

18h•$63,000 - $127,000•Hybrid

About The Position

The Senior Data Scientist is responsible for leading the development and implementation of machine learning models to solve complex business problems. This position works with large datasets, cleans and pre-processes data, and performs exploratory data analysis to understand the underlying patterns and trends. The Senior Data Scientist is also responsible for mentoring more junior Data Scientists, collaborating with cross-functional teams, and presenting findings and recommendations to senior leadership.

Requirements

PHD degree required in a Quantitative (heavy in mathematics, statistics or analysis, such as Applied Mathematics, Optimization, Psychology, or Economics) or Programming discipline.
2+ years of experience in data analysis.
1+ years of programming experience.
Significant experience working with large, complex data sets and common data science tools.
Experience working with database Python.
Experience designing, building, deploying, and validating machine-learning predictive models, ideally within a business framework.
Experience training multi model design to structure and train for unstructured data matching.
Experience training LLM models for specialized use cases
Highly inquisitive and self-motivated.
Ability to map out solutions with a starting point and end goal, but with few steps identified in-between.
Exceptional ability to analyze and synthesize data.
Advanced proficiency in SQL and Python.
Competency navigating and working within the AWS cloud suite.
Competency designing self-learning models that result in logarithm trends to identify trends in data to predict potential outcomes or missing data fields.
Core understanding of statistical concepts and methods.
Competency in the MS Office Suite.
Highly accountable and inquisitive, able to manage multiple tasks in a fast-paced, dynamic environment.
Self-motivated.
Excellent communication skills (written, verbal, and interpersonal) to coordinate across teams and deliver polished presentations.
Experience with training NumPy and Pandas models.

Responsibilities

Conduct advanced analyses and statistical deep dives, with a focus on producing actionable recommendations and strategic guidance for decision makers.
Develop and deploy custom models and algorithms using data and machine learning libraries to solve complex business problems.
Mine, clean, process, transform and join data from a variety of sources including SQL servers, AWS environments, SnowFlake, SalesForce, internal systems, and flat files.
Identify, wrangle, scrape, and assemble new data sources from the web, data aggregators, and public sources.
Build rich, interactive dashboards and visualizations from the ground up using PowerBI.
Compile and present key findings and reports to all levels of the organization, including senior leadership.
Continuously seek out opportunities to add value through process automation and programmatic solutions to manual tasks and monitor and improve Data Science model performance.
Act as a subject matter expert within the data science field. Continuously learn, grow, and explore new emerging technologies. (Stay up to date with industry trends and best practices.
Problem-solve, generate new ideas, and provide creative solutions.
Mentor, model, act as a resource, and provide guidance for more junior analysts and team members.
Lead development, testing and implementation of machine-learning models and algorithms using data and machine learning to solve complex business problems.