Data Scientist Level 2

Base-2 Solutions; Maryland; On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

401(k) with company match

Paid time off

Job summary

Base-2 Solutions is seeking a Data Scientist Level 2 to support the VISTA (MT&E Team). This role develops machine learning, data mining, statistical, and graph-based algorithms to analyze complex datasets, build and evaluate models, generate data-driven insights, and support the integration of analytics into production workflows.

The position partners with subject matter experts, software engineers, and cloud developers to translate mission needs into scalable analytic solutions.

Qualifications

• Active TS/SCI with Full Scope Polygraph is required.
• Proficiency in Python and R for data manipulation and algorithm implementation.
• Strong foundation in statistics and probability (regression, hypothesis testing).
• Knowledge of ML algorithms and frameworks such as TensorFlow and Scikit-Learn.
• Data wrangling and organizing complex datasets; SQL experience with PostgreSQL/MongoDB.
• Experience with data visualization tools like Tableau and Matplotlib.
• Bachelor’s degree in a quantitative field; 5+ years in analytics and data programming.
• Five years of experience analyzing datasets and developing analytics with R/Python/SAS/MATLAB.

Responsibilities

• Produce data visualizations to reveal data structure and meaning.
• Work with SMEs to extract information from SQL tables, metadata, and logs.
• Convert SME input into feature vectors for analytic development.
• Translate qualitative processes into quantitative software solutions.
• Develop and apply statistical, ML, and heuristic methods for descriptive and predictive analytics.
• Perform statistical tests to guide data-driven decisions and recommendations.
• Design experiments to collect data or simulate models when data is lacking.
• Create feature vectors for ML inputs and tune models accordingly.
• Select appropriate algorithms and optimize parameters for datasets.
• Validate analytics with cross-validation, ROC, and confusion matrices.
• Lead analytic efforts and guide scalable development across the team.
• Collaborate with software and cloud engineers to productionize analytics.
• Develop and train ML systems based on data characteristics to support mission automation.

Skills

Python

R

Statistics

Machine Learning

SQL

Tableau

Matplotlib

TensorFlow

Scikit-Learn

Education

Bachelor's Degree in quantitative discipline

Master's Degree

PhD

Associate Degree with 9 years experience

Tools

TensorFlow

Scikit-Learn

PostgreSQL

MongoDB

Job description

• Required Security Clearance: Top Secret/SCI with Full Scope Polygraph
• Location: Annapolis Junction, MD
• Work Type: On-Site
• Shift: First

• Standard Title: Junior Data Scientist
• Location: Annapolis Junction, MD
• Work Type: On-Site
• Shift: First
• Referral Eligibility: Eligible
• U.S. Citizenship Required? Yes

Position Summary

Base-2 Solutions is seeking a Data Scientist Level 2 to support the VISTA (MT&E Team). This role develops machine learning, data mining, statistical, and graph-based algorithms to analyze complex datasets, build and evaluate models, generate data-driven insights, and support the integration of analytics into production workflows. The position partners with subject matter experts, software engineers, and cloud developers to translate mission needs into scalable analytic solutions.

Essential Duties And Responsibilities

• 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, including SQL tables, structured metadata, and network logs.
• Incorporate SME input into feature vectors suitable for analytic development and testing.
• Translate customer qualitative analysis processes and goals into quantitative formulations 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, including cross-validation, ROC curves, and confusion matrices.
• Oversee the development of individual analytic efforts and guide the team in the 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.

Required Qualifications

• Active TS/SCI with Full Scope Polygraph.
• Proficiency in programming languages such as Python and R for data manipulation, analysis, and algorithm implementation.
• Strong foundation in statistics and probability, including regression analysis, hypothesis testing, and statistical distributions.
• Knowledge of machine learning algorithms and frameworks, such as TensorFlow and Scikit-Learn.
• Ability to perform data wrangling, including cleaning, transforming, and organizing complex datasets into usable formats.
• Familiarity with SQL and database management systems such as PostgreSQL and MongoDB.
• Experience with data visualization tools such as Tableau and Matplotlib.
• Bachelor's degree from an accredited college or university in a quantitative discipline, such as statistics, mathematics, operations research, engineering, or computer science.
• Five (5) years of experience analyzing datasets and developing analytics.
• Five (5) years of experience programming with data analysis software such as R, Python, SAS, or MATLAB.

Preferred Qualifications

• Experience partnering with software engineers and cloud developers to develop production analytics.
• Experience guiding analytic development efforts toward scalable solutions for large datasets.
• Experience translating customer qualitative analysis processes into quantitative software-based solutions.

Required Education and Experience Equivalency

• High School Diploma/GED with 9 years of experience.
• Associate Degree with 9 years of experience.
• Bachelor's Degree with 5 years of experience.
• Master's Degree with 5 years of experience.
• PhD with 1 years of experience.

Required Certifications

• None specified.

Required Security Clearance

• Active TS/SCI with Full Scope Polygraph.

Pay & Benefit Highlights

Compensation

• Competitive fixed salary or hourly pay (based on experience, skills, location, and internal equity).
• Employee referral bonuses up to $10,000 per hired referral.
• Additional bonus opportunities for exceptional performance and contributions to business development and company growth (role-dependent).

Health

• 100% company-paid medical premiums for employees and eligible dependents.
• Choose from multiple plan options with CareFirst, Kaiser, and UnitedHealthcare, including PPO, POS, HMO, and HSA-compatible plans.
• 100% company-paid dental premiums for employees and eligible dependents.
• 100% company-paid vision premiums for employees and eligible dependents.

Income Protection

• 100% company-paid premiums for short-term disability.
• 100% company-paid premiums for long-term disability.
• 100% company-paid premiums for accidental death & dismemberment (AD&D).
• 100% company-paid premiums for life insurance up to $200,000.

Retirement

• 401(k) with immediate vesting: 4% company match plus a 4% non-elective company contribution (8% total).
• 401(k) pre-tax and Roth options.

Leave

• Up to 20 days of flexible paid time off (PTO).
• 11 paid floating holidays.

Work-Life Balance

• Flexible work schedules, including flex time and compressed work periods (contract and project-dependent).