Data Scientist (Entry Level to SME) TSSCI with Poly REQUIRED

CGI Federal has an exciting opportunity for Data Scientists within our Intel sector advancing the national security mission through cutting edge technology. You must have a passion for keeping pace with rapidly evolving technology advancements and leveraging your knowledge on a highly collaborative team to deliver state-of-the-art capabilities.

The Data Scientist supports the analytics team by cleaning messy data running queries and helping to identify business trends. They focus on foundational tasks like Exploratory Data Analysis (EDA) and assist senior staff in preparing datasets for predictive models.

CGI Federal is growing its high-performance team whose members share a passion for building high-quality scalable advanced IT solutions in a collaborative fast-paced outcome-driven mission.

This position is located in our Arlington office; however a hybrid working model is acceptable.

Key Responsibilities (Entry Level)
Data Preparation: Use SQL to extract raw data and Python or R to clean and format datasets.
Exploratory Analysis: Analyze data to find trends patterns and anomalies.
Visualization: Create basic charts and dashboards using tools like Tableau or Python libraries to present findings to the team.
Model Assistance: Help senior data scientists train test and evaluate basic machine learning algorithms.

Key Responsibilities (Junior Level)
Data Wrangling: Clean process and validate raw structured and unstructured data to ensure uniformity and accuracy.
Exploratory Data Analysis (EDA): Analyze data to identify trends patterns and anomalies.
Modeling: Assist in developing testing and updating basic machine learning models and statistical algorithms.
Visualization & Communication: Build dashboards and presentations to clearly communicate findings and recommendations to both technical and non-technical stakeholders.
Pipeline Maintenance: Collaborate with data engineers and senior data scientists to maintain and optimize data pipelines

Key Responsibilities (Mid-Level)
Model Development & Deployment: Design train evaluate and deploy robust machine learning and deep learning models to solve ambiguous business problems.
Advanced Analytics: Conduct rigorous exploratory data analysis (EDA) and apply complex statistical techniques (e.g. A/B testing regression analysis clustering) to extract deep insights.
Data Engineering & Pipelines: Extract clean and manipulate unstructured datasets across distributed systems. Contribute to the design and optimization of data pipelines.
Stakeholder Collaboration: Translate high-level business goals into precise data science requirements. Present actionable recommendations to both technical and non-technical stakeholders.
Technical Leadership: Act as a subject matter expert and mentor junior analysts or entry-level data scientists on methodology and coding best practices.

Key Responsibilities (Senior Level)
Advanced Modeling: Architect and deploy Deep Learning (DL) Natural Language Processing (NLP) and Large Language Models (LLMs).
System Scalability: Build and optimize distributed data processing pipelines (e.g. using Spark) and automate reproducible workflows.
Translational Strategy: Convert ambiguous high-dimensional business/mission requirements into strict technical requirements.
Leadership & Mentorship: Lead end-to-end projects autonomously and mentor junior data scientists and engineers

Key Responsibilities (SME Level)
Advanced AI & Model Architecture: Architect and operationalize complex Agentic AI systems and customized Retrieval-Augmented Generation (RAG) frameworks to support dynamic domain requirements.
Constrained Environment Optimization: Optimize resource-heavy machine learning models and deep neural networks to perform reliably at the edge or within restricted computing ecosystems.
Unstructured Data Synthesis: Develop reproducible analytical models and quantitative techniques to draw definitive conclusions from incomplete noisy or highly unstructured raw datasets.
Pipeline Automation: Design and automate scalable data pipelines applying CI/CD principles to transition experimental prototypes seamlessly into enterprise production environments.
Statistical Rigor: Perform exhaustive statistical modeling hypothesis testing inference and probabilistic forecasting using multi-variate domain knowledge.

All levels require an active TS/SCI with Poly

Entry Level:
Education:
oHigh School Diploma/GED with 4 years of relevant experience
oAssociates Degree with 2 years of relevant experience
oor Bachelors Degree with 0 years of relevant experience
Programming: Working knowledge of Python R or SQL.
Math & Stats: Basic understanding of probability descriptive statistics and linear algebra.

Junior Level/Moderate:
Education:
oHigh School Diploma/GED with 6 years of relevant experience
oAssociates Degree with 4 years of relevant experience
oBachelors Degree with 2 years of relevant experience
oor Masters Degree with 0 years of relevant experience
Programming Skills: Strong proficiency in querying databases using SQL and coding in Python or R.
Statistical Knowledge: Foundational understanding of descriptive statistics probability and hypothesis testing.
Visualization Tools: Familiarity with BI and charting tools like Tableau Power BI or Python libraries (e.g. Matplotlib Seaborn)

Mid-Level/Complex:
Education:
oHigh School Diploma/GED with 8 years of relevant experience
oAssociates Degree with 6 years of relevant experience
oBachelors Degree with 4 years of relevant experience
oor Masters Degree with 2 years of relevant experience
oor PhD with 0 years of relevant experience
Programming: Advanced proficiency in Python or R and mastery of SQL for data extraction and manipulation.
Machine Learning Libraries: Hands-on experience with core ML frameworks such as scikit-learn TensorFlow PyTorch or XGBoost.
Data & Visualization: Experience using BI tools (e.g. Tableau Power BI) and libraries like pandas NumPy matplotlib or seaborn.
Foundations: Strong theoretical and practical understanding of statistical distributions probability and experimental design.

Senior Level/Exceptionally Complex:
Education:
oHigh School Diploma/GED with 10 years of relevant experience
oAssociates Degree with 8 years of relevant experience
oBachelors Degree with 6 years of relevant experience
oor Masters Degree with 4 years of relevant experience
oor PhD with 2 years of relevant experience
Technical Stack: Advanced proficiency in Python R and SQL. Hands-on experience with cloud computing platforms (AWS Azure) and Big Data environments.

SME Level/Exceptionally Complex:
Education:
oHigh School Diploma/GED with 12 years of relevant experience
oAssociates Degree with 10 years of relevant experience
oBachelors Degree with 8 years of relevant experience
oor Masters Degree with 6 years of relevant experience
oor PhD with 4 years of relevant experience
Languages & Environments: Expert-level proficiency in Python (including advanced use of Pandas NumPy and PyTorch/TensorFlow) and experience working natively in environments like Jupyter Notebooks and Databricks.
Foundational Math: Deep understanding of multi-variable calculus linear algebra and advanced probability/ Methodologies: Extensive hands-on background in constructing sophisticated algorithms including Large Language Models (LLMs) natural language processing and deep learning architectures.
Data Infrastructure: Advanced ability to clean curate and manipulate massive petabyte-scale datasets spanning multiple relational NoSQL and big data architectures.
Domain Context: Experience in highly specialized domains such as SIGINT/RF processing quantitative finance or complex biomedical analytics (dependent on industry).

CGI is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range includes various factors not limited to skill set level experience relevant training and licensure and certifications. To support the ability to reward for merit-based performance CGI typically does not hire individuals at or near the top of the range for their role. Compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for this role in the U.S. is $89600.00 - $204000.00.

CGI Federals benefits are offered to eligible professionals on their first day of employment to include:
. Competitive compensation
. Comprehensive insurance options
. Matching contributions through the 401(k) plan and the share purchase plan
. Paid time off for vacation holidays and sick time
. Paid parental leave
. Learning opportunities and tuition assistance
. Wellness and Well-being programs

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