Data Scientist

🕒 July 28

🇺🇸 United States – Remote

💵 $113k - $188k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

🦅 H1B Visa Sponsor

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Logo of Guidehouse

Guidehouse

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-based governance practices • Monitor deployed models for performance, drift, data quality, usage patterns, and operational issues; recommend retraining, tuning, or retirement • 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 within the platform

🎯 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, including 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 integration of 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, communicate recommendations clearly, 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 to translate analytical prototypes into scalable, maintainable solutions • 2+ years of hands-on experience with the Databricks platform is nice to have • Active Databricks Machine Learning Engineer, GenAI Engineer, Data Analyst, or related certification is nice to have • Experience with Databricks MLflow, Feature Engineering, Feature Store, Model Serving, Workflows, Unity Catalog, Mosaic AI, Vector Search, AI Gateway, or related Databricks AI/ML capabilities is nice to have • Experience developing GenAI, LLM, RAG, agentic AI, or prompt evaluation workflows is nice to have • Experience with CI/CD, automated testing, code packaging, environment promotion, and source control practices is nice to have • Experience with machine learning frameworks and statistical modeling techniques is nice to have • Experience with cloud platforms such as Azure, AWS, or GCP is nice to have • Experience working in project-based or consulting delivery environments is nice to have • Familiarity with data modeling, data warehousing, and large-scale data processing concepts is nice to have

🏖️ Benefits

• Comprehensive total rewards package • Competitive compensation • Flexible benefits package • Reasonable accommodation support

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