Overview:
** Hybrid, must reside in the Washington D.C. area for weekly onsite work. **
Come join a company that strives for Extraordinary People and Exceptional Performance! Chenega Services & Federal Solutions, LLC, a Chenega Professional Services’ company, is looking for a Data Scientist II to join our team of IT experts at the Federal Housing Finance Agency's (FHFA) Office of the Chief Information Officer (OCIO). As a mid-level Data Scientist, you will be working with large datasets, developing predictive models, conducting in-depth statistical analyses, and providing actionable insights to drive business decisions. The Data Scientist II will be expected to contribute to the development and deployment of machine learning models, refine analytical techniques, and collaborate cross-functionally with engineers, product managers, and other stakeholders. This is an excellent opportunity to grow your data science expertise in a collaborative and fast-paced environment.
Our company offers employees the opportunity to join a team where there is a robust employee benefits program, management engagement, quality leadership, an atmosphere of teamwork, recognition for performance, and promotion opportunities. We actively strive to channel our highly engaged employee’s knowledge, critical thinking, innovative solutions for our clients.
Responsibilities:
- Conduct exploratory data analysis (EDA) to identify trends, patterns, and anomalies in large datasets.
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Develop, implement, and maintain machine learning models (supervised, unsupervised, and reinforcement learning) to solve business problems.
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Work with complex structured and unstructured data (e.g., text, images, time series).
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Implement and evaluate different statistical models, algorithms, and techniques (e.g., regression, classification, clustering, NLP).
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Utilize feature engineering techniques to optimize models for production.
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Work closely with business stakeholders, product teams, and engineers to understand business goals and translate them into data-driven solutions.
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Communicate technical findings and model results clearly to non-technical stakeholders through visualizations and reports.
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Provide ongoing support for the deployment and monitoring of models in production.
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Conduct model validation using cross-validation techniques, A/B testing, and performance metrics.
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Optimize model performance through hyperparameter tuning, cross-validation, and other optimization strategies.
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Regularly monitor and update models to ensure they perform effectively over time (model drift, concept drift).
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Use data science tools and libraries such as Python (NumPy, pandas, scikit-learn), R, SQL, and/or other languages for data manipulation, analysis, and visualization.
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Work with big data tools such as Spark, Hadoop, or cloud platforms (AWS, GCP, Azure) as required.
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Create and maintain dashboards, reports, and other data visualizations using tools like Tableau, Power BI, or custom solutions.
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Stay up-to-date with the latest research, techniques, and technologies in data science, machine learning, and artificial intelligence.
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Collaborate with junior data scientists to guide and mentor them in data science methodologies and tools.
Qualifications:
- Bachelor's Degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field – or equivalent experience. Master’s Degree preferred.
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2-4 years of experience as a data scientist or in a similar analytical role with hands-on experience in building and deploying machine learning models.
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Strong experience with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) and data manipulation tools (e.g., pandas, NumPy).
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Familiarity with database systems (SQL and NoSQL) and experience working with large datasets.
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Experience working with cloud-based tools and platforms (AWS, Google Cloud, Azure) is a plus.
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Proficiency in Python, R, and/or other data science programming languages.
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Strong knowledge of statistical analysis, hypothesis testing, and data modeling techniques.
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Solid understanding of algorithms, optimization, and machine learning theory.
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Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau).
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Experience with version control (e.g., Git) and collaboration tools (e.g., JIRA, Confluence).
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Strong problem-solving skills with the ability to approach complex business problems with data-driven solutions.
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Ability to translate complex technical results into clear, actionable insights for business stakeholders.
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Experience presenting reults to both technical and non-technical audiences
Preferred Skills:
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Experience with advanced machine learning techniques (e.g., deep learning, NLP, reinforcement learning).
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Experience in specialized domains such as natural language processing (NLP), computer vision, or time-series forecasting.
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Familiarity with DevOps practices for model deployment and monitoring in production environments.
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Knowledge of model explainability and interpretability techniques.
Final salary determination based on skill-set, qualifications, and approved funding.
Many of our jobs come with great benefits – Some offerings are dependent upon the role, work schedule, or location, and may include the following:
Paid Time Off
PTO / Vacation – 5.67 hours accrued per pay period / 136 hours accrued annually
Paid Holidays - 11
California residents receive an additional 24 hours of sick leave a year
Health & Wellness
Medical
Dental
Vision
Prescription
Employee Assistance Program
Short- & Long-Term Disability
Life and AD&D Insurance
Spending Account
Flexible Spending Account
Health Savings Account
Health Reimbursement Account
Dependent Care Spending Account
Commuter Benefits
Retirement
401k / 401a
Voluntary Benefits
Hospital Indemnity
Critical Illness
Accident Insurance
Pet Insurance
Legal Insurance
ID Theft Protection
Teleworking Permitted?: true Teleworking Details: Hybrid, must reside in the Washington D.C. area and report onsite weekly Estimated Salary/Wage: USD $119,000.00/Yr. Up to USD $155,000.00/Yr.