Job description for Data Scientist at 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.
