Data Scientist, Databricks

🔥 11 minutes ago

⛰️ Colorado, District of Columbia, +5 more states – Remote

⛰️ Colorado – Remote 🏛️ District of Columbia – Remote 🌽 Illinois – Remote 🗽 New York – Remote 🍂 Massachusetts – Remote 🤠 Texas – Remote ⚔️ Virginia – Remote

💵 $113k - $188k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

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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 to support business and mission needs 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 platforms • 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 model governance practices • Monitor deployed models for performance, drift, data quality, usage patterns, and operational issues; recommend retraining, tuning, or retirement actions as needed • Analyze data to identify trends, patterns, and insights to support business decisions • Translate business requirements into analytical approaches, models, and data science solutions • Perform data validation, quality checks, and issue resolution to ensure accuracy and consistency • Collaborate with cross-functional teams including data engineers, analysts, and business stakeholders • Communicate model outputs, analytical findings, and recommendations to both technical and non-technical audiences • Document models, datasets, and methodologies to support 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 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 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.

🏖️ Benefits

• Competitive compensation • Flexible benefits package • Supportive workplace