layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

LAYIQ - Associate Data Scientist, DIBI at Northeastern University

Education & Experience
Required
Master’s degree in Data Science, Statistics, Computer Science Computer Science, Applied Mathematics, or a closely related field
2–4 years of professional experience in software engineering, data science, or applied R&D, with exposure to machine learning and AI system development in research, prototype, or production environments.
Preferred
Master’s degree or Ph.D with a focus on data science, data ‑ intensive systems, network science, optimization, or related areas.
Experience contributing to government, defense, or security ‑ related R&D programs (internships, fellowships, or full ‑ time roles).
Familiarity with simulation ‑ based models (e.g., physics ‑ based, network ‑ based, agent ‑ based, or stochastic simulations) for analysis, experimentation, or decision support.
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Skills & Attributes
Required
Advanced proficiency in Python and/or R studio and familiarity with modern ML/AI development workflows.
Exposure to C++ and/or Java for performance‑critical components
Experience contributing to the design, implementation, testing, or evaluation of ML/AI-enabled or simulation-drive software systems.
Demonstrated experience with data visualization and reporting tools (e.g., Tableau, Power BI, matplotlib, Plotly), including designing dashboards for executive or sponsor audiences.
Proven experience independently building, validating, and interpreting statistical or machine learning models, and communicating tradeoffs to non-technical stakeholders.
Strong command of data cleaning, ETL processes, and data quality assurance practices, including for messy or incomplete real-world datasets.
Solid software engineering fundamentals, including version control (e.g., Git/GitHub), documentation, and reproducibility.
Excellent written and verbal communication skills, with experience presenting analytical findings directly to leadership or sponsors.
U.S. Citizenship with the ability to obtain and maintain a security clearance
Desired: Exposure to Retrieval‑Augmented Generation (RAG), vector databases, embedding pipelines, or LLM‑enabled systems.
Familiarity with cloud computing environments (e.g., Azure, AWS or GovCloud equivalents).
Introductory experience with graph‑based ML or GNNs is a plus
Monte Carlo or stochastic simulation methods
Synthetic data generation or simulation‑in‑the‑loop workflows
Familiarity with geospatial data, spatiotemporal datasets, or PostgreSQL/PostGIS is a plus.
Interest in UI or frontend development for technical or analyst‑facing tools (e.g., Svelte , React, or similar frameworks).
Exposure to dashboarding or BI tools for analyst-facing or leadership-facing reporting
Familiarity with MLOps concepts, experiment tracking, or reproducible research pipelines.
Experience working with multidisciplinary teams across research, engineering, and applied R&D environments.

Associate Data Scientist, DIBI

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