Kasmo Inc.

Kasmo Inc.

Data Scientist (W2 Only)

Camden, New Jersey, USA · Contract

Sponsorship not specifiedDetected 63 days ago
PythonAlgorithmsSQLNoSQLAWSGCPAzureCloud PlatformsDockerKubernetesDevOpsKafkaMachine LearningDeep LearningTensorFlowPyTorchscikit-learnSparkData EngineeringData ScienceData VisualizationNLPComputer VisionMLOps

About the role

  • Apply statistical analysis and visualization techniques (hierarchical clustering, principal components analysis (PCA)) to explore and prepare data.
  • Select appropriate algorithms and models for AI /ML, and rigorously test them for accuracy, robustness, and fairness.
  • Integrate domain knowledge into ML solutions (e.g., care delivery, financial risk, customer journey, quality prediction, sales, marketing).

Responsibilities

  • Acquire access to various databases and source systems (SQL, NoSQL, graph databases) and create data pipelines for efficient and repeatable data science projects.
  • Perform feature selection and engineering, create predictive variables, and experiment with transformations to enhance performance and interpretability.
  • Collaborate with MLOps, data engineers, and IT to evaluate deployment options, and establish best practices around ML production infrastructure.
  • Create dashboards, and interactive visualizations that communicate results to a wide range of audiences, turning technical findings into actionable recommendations.
  • This role involves analyzing large datasets, developing AI /ML /optimization models, and translating findings into actionable insights.
  • The Data Scientist partners with business and operational leaders, supports senior leadership with analytics, and fosters a culture of data-driven decision-making across the organization.

Nice to have

  • Specialization in ML, AI, cognitive science, or data science is highly preferred.

Benefits

  • The Data Scientist plays a pivotal role in planning, executing, and delivering machine learning-based projects that drive business impact.
  • Design, develop, and validate machine learning, statistical, and optimization models for classification, regression, clustering, recommendation, and prediction tasks.
  • Continuously monitor execution and health of production ML models, recalibrating as needed and updating them to reflect new data or changing business conditions.
  • Qualifications Education Master’s, or PhD in Computer Science, Data Science, Engineering, Statistics, Applied Mathematics, Operations Research, or a related quantitative field.
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