Data Scientist III

Reflexive Concepts; Maryland; On-site; USD 120,000 - 180,000; Full time

Job summary

Reflexive Concepts is seeking a Data Scientist III to join our growing team in Maryland. The role focuses on developing machine learning, data mining, and statistical algorithms to analyze datasets and generate data-driven insights for customers.

You will prototype multiple algorithms, select the best performing model, and translate SME input into scalable analytics within production frameworks. Strong collaboration with SMEs and engineers is essential for success.

Qualifications

• Bachelor's degree in a quantitative discipline or higher.
• 10+ years in ML/AI/data analytics with tools like R, Python, SAS or MATLAB.

Responsibilities

• Develop ML, data mining, and statistical algorithms to analyze datasets.
• Prototype and select final models based on performance metrics.
• Build experiments or data generators when data is scarce.
• Create reports and visualizations to provide data-driven insights to customers.
• Translate SME input into automated analytics and production-ready workflows.
• Lead production analytics development with software and cloud engineers.

Skills

MLOps

Data science

Data visualizations

SME collaboration

Feature engineering

Statistical analysis

Education

Bachelor's degree in quantitative field

Doctoral/_master substitution options

Tools

Python

R

SQL

SAS/MATLAB

Job description

Reflexive Concepts is seeking a skilled Data Scientist III to join our growing team!

The Data Scientist will develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows.

Qualifications:

• Bachelor's degree or higher from an accredited college or university in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science).
  • An additional four (4) years of experience in software development, cloud development, analyzing datasets, or developing descriptive, predictive, and prescriptive analytics can be substituted for a Bachelor's degree.
  • A Master’s Degree from an accredited college or university in a quantitative discipline can be substituted for two (2) years of experience for a total of eight (8) years of experience required.
  • A Doctoral Degree from an accredited college or university in a quantitative discipline can be substituted for four (4) years of experience for a total of six (6) years of experience required.
• A minimum of ten (10) years of experience in two (2) or more of the following: designing/implementing machine learning, data mining, advanced analytical algorithms, advanced statistical analysis, artificial intelligence, or software engineering with data analysis software such as R, Python, SAS, or MATLAB.

Required:

• Significant MLOPS and Data Science background
• Produce data visualizations that provide insight into dataset structure and meaning
• Work with subject matter experts (SMEs) to identify important information in raw data and develop scripts that extract this information from a variety of data formats (e.g., SQL tables, structured metadata, network logs)
• Incorporate SME input into feature vectors suitable for analytic development and testing
• Translate customer qualitative analysis process and goals into quantitative formulations that is coded into software prototypes
• Develop and implement statistical, machine learning, and heuristic techniques to create descriptive, predictive, and prescriptive analytics
• Develop statistical tests to make data-driven recommendations and decisions
• Develop experiments to collect data or models to simulate data when required data are unavailable
• Develop feature vectors for input into machine learning algorithms
• Identify the most appropriate algorithm for a given dataset and tune input and model parameters
• Evaluate and validate the performance of analytics using standard techniques and metrics (e.g. cross validation, ROC curves, confusion matrices)
• Oversee the development of individual analytic efforts and guide team in analytic development process
• Guide analytic development toward solutions that can scale to large datasets
• Partner with software engineers and cloud developers to develop production analytics
• Develop and train machine learning systems based on statistical analysis of data characteristics to support mission automation
• Lead a team of data scientists in the development of multiple analytic efforts
• Work with customers and SMEs to define analytic requirements and guide the team in formulating analytics that meet requirements
• Guide the transition of prototyped analytics to production system
• Understand emerging machine learning and pattern recognition algorithms and guide a team of data scientists in integrating state-of-the-art algorithms into solutions
• Delegate analysis responsibilities to one or more team members and monitor performance