Data scientist
Core
Design and implement data science solutions, develop advanced analytical models, and lead data science aspects of customer implementations and production deployments.
Role type
Customer-facing data scientist (machine learning & analytics)
Builds
Predictive modeling initiatives, advanced analytics workflows, and scalable ML solutions for customers
Domain
Financial services, fraud detection, risk analytics, compliance, transaction monitoring (via careerplan.io/jobs/19-00F-57-377-data-scientist-at-matrix-global)
Deliverable
production ML models
Required skills
Python, PySpark, Apache Spark, Machine Learning, MLflow, Airflow, SQL, Feature Engineering, Statistical Analysis, Large-scale data processing
Preferred skills
Financial services domain expertise, Cloud-based ML environments, Anomaly investigation, Model deployment and monitoring
Technologies
Python, PySpark, Apache Spark, MLflow, Airflow, SQL
Responsibilities
Design and implement data science solutions throughout the project lifecycle; Analyze large and complex datasets to identify trends and actionable insights; Develop and optimize machine learning models and advanced analytics workflows; Perform feature engineering and data preparation for predictive modeling; Collaborate with Product, Engineering, and Customer Success teams to translate business requirements into technical solutions; Lead the data science aspects of customer implementations, pilots, and production deployments; Provide recommendations to improve products, algorithms, and analytical capabilities; Deliver training and knowledge transfer to end users and stakeholders; Support investigation and resolution of data-related and analytical challenges.
Seniority
Mid-level, hands-on IC
