AI/ML Data Scientist

Virtusa

. Frame business problems as machine learning tasks .

Posted 11/12/2026full-timeRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying machine learning models, with strong proficiency in Python and SQL. Capable of conducting exploratory data analysis and communicating insights effectively to non-technical stakeholders.

Highest-signal resume keywords

Machine Learning Model DevelopmentPython ProficiencySQL ProficiencyFeature EngineeringCloud Data Environments

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Gradient BoostingTime-Series ForecastingRegressionClusteringNatural Language ProcessingExploratory Data AnalysisModel Evaluation MetricsExperimental DesignData Drift MonitoringModel Degradation Monitoring

Soft Skills

CommunicationCollaborationPragmatic Mindset

Tools & Technologies

Scikit-learnXGBoostLightGBMPyTorchTensorFlowStatsmodelsPandasDatabricksSnowflakeAWS

Industry Keywords

MLOpsMLflowGit

Tech Stack

Tools & technologies

AWSAzureCloudPandasPythonPyTorchScikit-LearnSnowflakeSQLTensorflow

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

Remote work
Full-time employment