Job Title
Data Scientist
Job Responsibilities
Analyze structured and unstructured data to identify trends, patterns, and correlations.
Translate complex data findings into clear and actionable insights for stakeholders.
Collect, process, and clean large datasets to ensure quality and consistency.
Develop automated data pipelines for streamlined data access.
Build, test, and deploy machine learning models to solve business challenges.
Perform feature engineering and optimize models for accuracy and performance.
Conduct hypothesis testing and use statistical methods to validate findings.
Develop algorithms and statistical models to support decision-making.
Work closely with stakeholders to understand business objectives and translate them into data science projects.
Present results through dashboards, reports, and visualizations.
Use programming languages such as Python, R, or SQL for data manipulation and analysis.
Leverage big data tools (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP) as needed.
Stay updated on the latest data science trends, tools, and methodologies.
Experiment with emerging technologies to improve current processes and solutions.
Educational Qualification
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. Certifications in data science or machine learning (e.g., Google Data Engineer, AWS Certified Machine Le
arning) are a plus.
Experience Requirements
2+ years of experience in data science or a related analytical role.
Demonstrated success in solving real-world problems through data science projects.
Additional Requirements
Strong programming skills in Python, R, or similar languages.
Proficiency in SQL for database querying and management.
Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
Familiarity with data visualization tools (e.g., Tableau, Power BI, Matplotlib).
Knowledge of big data platforms (e.g., Hadoop, Spark) and cloud services.
Expertise in statistical analysis, data modeling, and algorithm design.
Strong problem-solving abilities to derive insights from ambiguous data.
Excellent communication and presentation skills to convey complex data insights to non-technical audiences.
Team-oriented with the ability to collaborate effectively across departments.