AI/ML Data Scientist

🔥 29 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 10%

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• No salary listed.

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Virtusa

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1996

💼 Consulting

🏢 Enterprise

🤖 Artificial Intelligence

💰 $108M Post-IPO Equity - Virtusa on 2017-05

Consulting • Enterprise • Artificial Intelligence

Virtusa is a global technology services and consulting company that helps enterprises reimagine their business through digital engineering, AI-driven and domain-focused solutions. It offers consulting, design, engineering, automation, analytics and optimization services, and partners with organizations across banking & financial services, communications, healthcare, insurance, retail, manufacturing and other industries to deliver enterprise-scale technology and AI solutions. Virtusa emphasizes AI services, domain-driven solutions for the AI enterprise, and end-to-end digital transformation.

📋 Description

• Frame business problems as machine learning tasks • Conduct exploratory data analysis on large-scale structured datasets • Develop, train, and validate predictive models, including gradient boosting, time-series forecasting, regression, clustering, and NLP • Build reproducible feature engineering and model training pipelines in Python and SQL • Collaborate with Data Engineers to deploy models into production • Implement automated monitoring for data drift and model degradation • Communicate model insights, confidence intervals, and business impact clearly to non-technical stakeholders • During onboarding, adjust working hours to overlap with US hours until 7:00 PM at the latest

🎯 Requirements

• 4+ years of hands-on experience building and deploying classical machine learning and statistical models in production • Strong proficiency in Python, including scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow, statsmodels, and pandas • Strong proficiency in SQL • Solid foundation in statistics • Experience with experimental design (A/B testing) • Experience with feature engineering and model evaluation metrics • Experience working in cloud data environments such as Databricks, Snowflake, AWS, or Azure • Experience using MLOps tools such as MLflow and Git • Pragmatic mindset focused on choosing the simplest, most reliable model that solves the business problem

🏖️ Benefits

• Remote work • Full-time employment

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