Statsmodels

Statsmodels Data Jobs

2 jobs found

1mo ago

Data Scientist

LMI Remote 🌍 Remote

Remote

1mo ago Closed

$90k - $150k/yr Full time Aws Serverless Bayesian Statistics Data Analysis

This position is no longer accepting applications (closed Sep 12, 2026).

Job Description

This senior-level Data Scientist role supports the Department of State Passport Bureau (CA/PPT) by designing, developing, evaluating, and monitoring forecasting models for US passport demand. The position focuses on statistical and time series methods, including econometric approaches, and requires translating results into insights for both technical and non-technical stakeholders.

Role Summary

Develop forecasting models that project US passport demand 23 to 36 months into the future. The work includes prototyping new modeling strategies, assessing data quality and assumptions, and maintaining ongoing evaluation and monitoring as conditions and inputs change.

Key Responsibilities

Design, develop, evaluate, and actively monitor statistical and time series models, including econometric approaches, to forecast demand 23 to 36 months ahead.
Rapidly prototype and iterate on new models, methodologies, and analytical libraries that use advanced statistical and related tools; assess strengths and limitations.
Critically evaluate data sources, modeling assumptions, and results; identify risks, biases, and sources of uncertainty.
Actively monitor passport demand signals, survey results, policy developments, and travel, economic, geopolitical, and other trends; explore ways to use these inputs to forecast impacts.
Translate complex analytical outcomes into clear, actionable insights for technical and non-technical stakeholders.
Work independently to explore novel approaches while maintaining methodological discipline and healthy skepticism.
Stay current on emerging technologies, tools, and best practices in forecasting, statistics, and data science.
Explore customer needs and identify opportunities to add value.

Requirements

Advanced degree (PhD or Masters) from an accredited college or university in a data-related field of study.
Strong communication skills to coordinate with senior leadership, peers, and staff across all levels.
Advanced experience in statistical analysis and time series modeling, including econometric techniques, seasonal regression, and other statistical models.
Demonstrated ability to think critically about models, data, and assumptions rather than relying on off-the-shelf solutions.
Strong problem-solving skills and comfort operating in ambiguous or evolving problem spaces.
Ability to learn new tools, frameworks, and technologies quickly and apply them effectively.
Proven track record of independent work and ownership of analytical projects.

Technologies

Python, statsmodels, pandas, numpy, xgboost, scipy, matplotlib
STATA
ARIMA, vector autoregression (VAR)
Bayesian statistical models
Cloud environments, including serverless technologies in the AWS cloud

Desired Attributes

Creative and innovative mindset with risk awareness and analytical rigor.
Willingness to challenge existing approaches while maintaining sound methodology.
Curiosity-driven learning with a pragmatic approach to adopting new technologies.
Comfort iterating quickly, testing ideas, and discarding approaches that do not meet standards.
Experience with Python statistics and machine learning framework and libraries, including statsmodels, pandas, numpy, xgboost, scipy, and matplotlib.
Experience working with STATA.
Experience applying time series statistical methods, including ARIMA and vector autoregression (VAR).
Experience applying machine-learning models to time series analysis in data-poor environments.
Experience applying Bayesian statistical models to time series analysis.
Experience leveraging cloud environments for data science tasks, specifically using serverless technologies in the AWS cloud.

Location and Compensation

Location: Remote (remote).
Compensation: USD 90,000 to 150,000 per year.

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1mo ago

Data Scientist

System One Minneapolis, MN

Minneapolis, MN

1mo ago Closed

Full time Python Artificial Intelligence Automation

This position is no longer accepting applications (closed Aug 27, 2026).

Job Description

System One is seeking a Data Scientist to design, build, and deploy production-grade machine learning models, bridging data science with software engineering to embed AI capabilities into enterprise products and systems in Minneapolis, onsite.

Location

Minneapolis, MN (onsite)

Role Overview

In this role, you will design, build, and deploy production-grade machine learning models while bridging data science with software engineering. The work focuses on delivering clean, modular Python code to embed AI capabilities within enterprise products and systems.

Responsibilities

Design, train, and validate predictive and analytical models across regression, classification, decision trees, time-series, and neural networks.
Implement scalable Python code to package models as microservices and expose them via REST APIs for real-time inference.
Create and maintain automated data preprocessing, feature engineering, and model evaluation pipelines aligned with CI/CD and MLOps best practices.
Monitor production models for performance, data drift, and latency to ensure ongoing reliability and accuracy.
Collaborate with executive leadership, product directors, and enterprise architects to shape the AI and ML product roadmap.

Requirements

5 to 7 plus years of hands-on experience developing and sustaining complex ML/AI solutions within enterprise production environments.
Experience deploying ML models into production settings.
Proficiency with core ML algorithms and frameworks such as scikit-learn, XGBoost, LightGBM, statsmodels, PyTorch, or TensorFlow.
Proven ability to deliver clean, modular, and object-oriented Python code that adheres to PEP 8 beyond notebook environments.
Experience with automated testing frameworks (pytest, unittest) and implementing unit and integration tests.
Practical experience building RESTful APIs with FastAPI or Flask.
Experience with Docker and version control workflows using Git, GitHub Actions, or GitLab CI/CD.
Advanced SQL skills and experience querying structured and unstructured data.
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related quantitative field.

Technologies

Python
scikit-learn
XGBoost
LightGBM
statsmodels
PyTorch
TensorFlow
FastAPI
Flask
Docker
Git
GitHub Actions
GitLab CI/CD
SQL

Benefits

Health and welfare benefits coverage options including medical, dental, vision
Spending accounts
Life insurance
Voluntary plans
401(k) plan

Preferred Qualifications

Generative AI and Enterprise LLMs: hands-on experience developing, fine-tuning (LoRA/QLoRA), or deploying proprietary Large Language Models (LLMs), agentic frameworks, custom embeddings, or enterprise RAG systems.
Experience with GPU acceleration frameworks (CUDA, TensorRT, vLLM, Ollama).
Demonstrated leadership in mentoring teams and defining enterprise data and AI governance policies.

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