Data Scientist: Craft ML Insights for Production

Columbia Technology Partners

Corridor North (MD)

On-site

USD 120,000 - 180,000

Full time

14 days+

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Benefits offered by this job

Medical plans

Vision + Dental

401(k) company contribution

Profit Sharing Bonus

Referral Bonus Program

Career Growth assistance up to $10,000

Job summary

Columbia Technology Partners is seeking Data Scientists to develop advanced analytics, machine learning models, and data‑driven solutions that transform complex datasets into actionable insights. You will collaborate with subject matter experts, engineers, and stakeholders to automate analytical workflows and deliver production‑ready analytic capabilities.

The role emphasizes building descriptive, predictive, and prescriptive analytics, data visualization, and scalable analytics across large

Qualifications

Bachelor's degree in Statistics, Mathematics, Operations Research, Engineering, Computer Science, or related field from an accredited college or university.
A Master's degree may substitute for two years of analytics experience and one year of programming experience.
A PhD may substitute for four years of analytics experience for Level 2 candidates.
Four additional years of relevant experience may substitute for a bachelor's degree.
Level 1 requires four years of analytics experience plus two years of programming with data analysis tools such as Python, R, SAS, or MATLAB.
Level 2 requires eight years of analytics experience plus five years of programming with Python, R, SAS, or MATLAB.

Responsibilities

Develop machine learning, statistical, graph‑based, and heuristic algorithms to analyze complex datasets.
Produce data visualizations that provide insight into data structure, trends, and operational relevance.
Collaborate with SME to identify valuable information within raw data sources and develop extraction methodologies.
Transform customer objectives and analytical processes into quantitative models and software‑based solutions.
Develop descriptive, predictive, and prescriptive analytics to support decision‑making and mission outcomes.
Design and execute statistical tests to support data‑driven recommendations and conclusions.
Create feature vectors and datasets suitable for analytics development, testing, and model training.
Generate reports, visualizations, and presentations that communicate findings and recommendations to stakeholders.
Partner with software engineers and technical teams to integrate analytical capabilities into operational workflows.
Implement prototype analytics and machine learning models within production environments.
Develop experiments and modeling approaches to generate or simulate training data when operational datasets are unavailable.
Identify, evaluate, and select appropriate machine learning algorithms for specific datasets and mission requirements.
Tune models and optimize performance using established validation techniques and performance metrics.
Evaluate analytic approaches and provide recommendations throughout the analytics development lifecycle.
Design analytics that scale effectively across large datasets and distributed environments.
Develop and train machine learning systems supporting automation and advanced mission capabilities.
Apply advanced validation techniques including cross‑validation, ROC analysis, confusion matrices, and other performance assessment methodologies.