Data Scientist

🕒 July 28

🇺🇸 United States – Remote

💵 $113k - $188k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 14%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Guidehouse

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 2018

🏥 Healthcare

🎖️ Defense

📦 Logistics

💰 Grant on 2023-02

Healthcare • Defense • Logistics

Guidehouse is a global consultancy offering advisory, digital, and managed services across commercial and public sectors. It is purpose-built to support industries such as national security, financial services, healthcare, energy, and infrastructure. Guidehouse collaborates with leaders to navigate complexity and drives transformational changes that impact the future. Their expertise spans data analytics, digital technologies, risk management, and more, with a strong emphasis on sustainability and innovation.

📋 Description

• Develop, train, and evaluate machine learning and statistical models using the Databricks platform • Prepare, clean, and maintain datasets for modeling, experimentation, and analysis • Write, optimize, and maintain Python and SQL workflows for data exploration, feature engineering, and model development • Work with large-scale datasets using Databricks, Spark, and Delta Lake • Design reusable feature engineering workflows and model training pipelines using Databricks notebooks, workflows, and MLflow • Register, version, promote, and document models using MLflow Model Registry and Unity Catalog governance practices • Monitor deployed models for performance, drift, data quality, usage patterns, and operational issues • Recommend model retraining, tuning, or retirement actions as needed • Analyze data to identify trends, patterns, and insights supporting business decisions • Translate business requirements into analytical approaches, models, and data science solutions • Perform data validation, quality checks, and issue resolution • Collaborate with data engineers, analysts, and business stakeholders • Communicate model outputs, analytical findings, and recommendations to technical and non-technical audiences • Document models, datasets, and methodologies for reproducibility, transparency, and reuse • Follow data governance, security, and compliance standards

🎯 Requirements

• Bachelor’s degree in computer science, engineering, mathematics, statistics, or another relevant field • 3–8 years of relevant experience in data science, machine learning, or advanced analytics • Strong experience with Python and SQL for data analysis, modeling, and transformation • Experience with Databricks, Spark, Delta Lake, or similar cloud-native data platforms • Hands-on experience designing, building, evaluating, and deploying machine learning models • Experience moving models from prototype to production or production-like environments • Experience with ML lifecycle practices including experiment tracking, model evaluation, model registry, version control, deployment workflows, monitoring, and retraining approaches • Familiarity with model serving patterns, API-based inference, scheduled batch scoring, and integrating model outputs into dashboards, applications, or operational workflows • Experience with data preparation, feature engineering, and model development • Ability to analyze data and communicate insights clearly • Ability to troubleshoot technical issues and work effectively in team-based delivery environments • Experience supporting AI governance practices, including model documentation, validation, monitoring, version control, and responsible AI considerations • Ability to work across data science, data engineering, cloud, security, and client stakeholder teams • Nice to have: 2+ years of hands-on Databricks experience • Nice to have: active Databricks Machine Learning Engineer, GenAI Engineer, Data Analyst, or related certification • Nice to have: experience with Databricks MLflow, Feature Engineering, Feature Store, Model Serving, Workflows, Unity Catalog, Mosaic AI, Vector Search, AI Gateway, or related capabilities • Nice to have: experience developing GenAI, LLM, RAG, agentic AI, or prompt evaluation workflows • Nice to have: experience with CI/CD, automated testing, code packaging, environment promotion, and source control • Nice to have: experience with machine learning frameworks and statistical modeling techniques • Nice to have: experience with Azure, AWS, or GCP • Nice to have: experience in project-based or consulting delivery environments • Nice to have: familiarity with data modeling, data warehousing, and large-scale data processing concepts

🏖️ Benefits

• Comprehensive, total rewards package • Competitive compensation • Flexible benefits package • Diverse and supportive workplace • Reasonable accommodation support