Data Scientist

• Deskripsi pekerjaan Data Scientist Sagara Technology
• Key Responsibilities
• Design, develop, and deploy machine learning and statistical models to create data-driven products, services, and revenue opportunities.
• Identify opportunities to monetize data through predictive models, scoring systems, APIs, and actionable insights.
• Build end-to-end machine learning pipelines, including data exploration, feature engineering, model development, validation, and deployment.
• Collaborate with product, business, and engineering teams to translate business requirements into measurable data science solutions.
• Define and track model performance metrics, business impact, and revenue-related KPIs.
• Monitor, maintain, and optimize deployed models to ensure performance, reliability, and scalability.
• Ensure data quality, governance, privacy, and security compliance throughout the modeling lifecycle.
• Present technical findings and business insights to both technical and non-technical stakeholders.
• Independently manage project priorities, timelines, and deliverables with minimal supervision.
• Provide guidance and mentorship to junior data scientists and analysts when required.

Requirements

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• Minimum 5 years of professional experience in Data Science or Machine Learning.
• Proven experience developing and deploying machine learning models into production environments.
• Strong proficiency in Python and/or R, SQL, and machine learning frameworks such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Solid understanding of statistical modeling, machine learning algorithms, feature engineering, and model evaluation.
• Experience managing end-to-end data science projects independently.
• Strong business acumen with the ability to translate analytical solutions into measurable business value.
• Excellent analytical, problem-solving, communication, and stakeholder management skills.
• Nice to Have
• Experience with big data technologies such as Spark or Hadoop.
• Familiarity with cloud platforms such as AWS, Google Cloud Platform (GCP), or Microsoft Azure.
• Experience developing data-driven products, monetization models, or revenue-generating solutions.
• Experience in fraud detection, anomaly detection, risk scoring, or transaction monitoring.
• Previous experience mentoring junior team members.