Data Scientist

The Data Scientist solves analytical and business problems using quantitative, statistical, mathematical, and technical approaches. This role researches, designs, implements, and validates algorithms to analyze diverse data sources and generate actionable insights. The Data Scientist applies statistical and predictive modeling techniques to support business decisions, improve processes, and deliver project-specific outcomes.
Key Responsibilities

- Apply data science methodologies to solve complex business problems and generate data-driven insights.

- Research, design, develop, implement, and validate statistical and predictive models and algorithms.

- Develop algorithms using statistical methodologies, programming languages, and data science tools.

- Clean, prepare, profile, and transform data to ensure quality and suitability for analysis and modeling.

- Perform data mining, exploratory analysis, and data visualization to identify relationships, patterns, trends, and anomalies.

- Develop and evaluate statistical and machine learning models for regression, classification, forecasting, anomaly detection, and other business applications.

- Partner with domain experts and cross-functional stakeholders to validate model capabilities, assumptions, and business relevance.

- Analyze complex requirements and data to determine appropriate analytical approaches, feasibility, and priorities.

- Clearly communicate analytical results, methodologies, assumptions, and recommendations to technical and non-technical stakeholders.

- Develop robust, data-based solutions and support systematic problem solving and root-cause analysis.

- Apply appropriate validation, testing, quality control, and model evaluation techniques to ensure reliable analytical solutions.

- Leverage emerging data science, digital, cloud, and technology solutions to continuously improve analytical capabilities.

- Contribute to the continuous development of the team through knowledge sharing, collaboration, and mentoring.

- Follow applicable business, technical, security, governance, compliance, and data regulations while developing and implementing solutions.

Qualifications

- College, university, or equivalent degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Technology, or another relevant technical discipline, or equivalent relevant experience.
- Relevant internship, co-op, temporary student employment, academic projects, or extracurricular team experience is preferred.