Engineering Technician - Carlsbad, CA Information Technology

SOC
Carlsbad, United States of America
4 days ago

Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 153K

Job location

Carlsbad, United States of America

Tech stack

Artificial Intelligence
Azure
Big Data
Computer Simulation
Information Systems
Data Visualization
Information Sciences
Python
Machine Learning
Open Source Technology
Zero Trust Network Access
Standard Sql
Azure
SAS (Software)
Stata
Statistics
Tableau
Unstructured Data
Feature Engineering
Data Ingestion
Large Language Models
Spark
Model Validation
Generative AI
Matplotlib
Information Technology
Statistics Packages
Data Analytics
Data Management
GPT
Databricks

Job description

Remote Senior Data Scientist is needed for a contract opportunity onsite with SOC's client Contract Duration: 6 Months, possible extension and/or FTE Clearance: Public Trust, Our is seeking a Senior Data Scientist who will work closely with client stakeholders to support economic analysis of national importance through application of advanced statistics and data science techniques and technologies. In this position, you will utilize your strong background in statistics, machine learning, generative AI, visualization, economic analysis, and big data processing to plan and execute projects to meet business client data needs. Requirements

  • Partner with stakeholders to scope questions and assumptions, support solution design, and facilitate project execution
  • Design and implement robust data ingestion, storage, integration, processing, retrieval, and management strategies for research datasets
  • Build transparent, reproducible pipelines and analysis environments in cloud infrastructures
  • Produce crisp exhibits and memos that explain methods, limitations, and uncertainty
  • Facilitate and execute data-driven research by applying sophisticated statistical, machine learning, and computational methods to analyze complex datasets related to computer and information science
  • Create compelling data visualizations and reports that convey complex research findings in a clear and accessible manner to both technical and non-technical stakeholders
  • Support defensible analytics and econometric/causal inference workstreams, translating ambiguous business or legal questions into testable hypotheses and clear, client-ready findings
  • Design and execute rigorous studies (e.g., difference-in-differences, panel models with fixed/random effects, instrumental variables/2SLS, time series/forecasting, etc.) to turn multi-source datasets into documented, auditable results
  • Mentor teammates on best practices
  • Stay updated on the latest academic research and industry advancements in data science, AI, and information systems, and apply relevant findings to ongoing projects

Requirements

  • Master's degree, PhD preferred in Statistics, Mathematics, or a related quantitative field, with 5-8+ years of applied data science experience
  • Mastery of Python or R, statistical tools such as Stata, SAS and strong SQL
  • Expertise with ML algorithms (e.g. model selection, evaluation, feature engineering, etc.)
  • Expertise with application of AI to deliver insights with optimal performance, cost savings, etc. using structured, unstructured data
  • Expertise with data visualization tools (e.g. Tableau, Matplotlib)
  • Experience processing large datasets, deploying LLMs in government cloud data platforms (e.g. Azure ADLS/Databricks/Azure ML, or equivalents)
  • Comparative understanding of LLMs (e.g. Claude Code, ChatGPT), and tradeoffs in terms of capabilities, cost, and performance
  • Excellent problem-solving skills and the ability to think critically and analytically to address complex research challenges
  • Exceptional verbal and written communication skills and a bias toward rigor, clarity, and defensibility over black-box modeling are essential
  • Familiarity with FISMA/NIST/Zero Trust security frameworks
  • Current Principal Data Scientist (PDS) Certification

Preferred

  • Experience with Spark/Databricks.
  • Domain exposure to antitrust, pricing, healthcare claims, fraud/forensics, or financial analysis is a plus.
  • Experience producing reproducible, peer-reviewed-method analyses that meet Rule 702/Daubert reliability requirements and can withstand Daubert challenges (methods, error rates, standards/controls, and appropriate bounds on conclusions)
  • Contribution to open-source projects or participation in relevant data science communities., The following requirements must be met to be eligible for this position: successful completion of a background investigation, and drug urinalysis.

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