Data scientist

at  KRIS INFOTECH PTE LTD

REQUIREMENTS:

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field (or equivalent practical experience).
• Proven experience as a Data Scientist or similar role, with a portfolio of data science projects that demonstrate your analytical skills.
• Proficiency in programming languages such as Python or R for data manipulation and analysis.
• Strong understanding of statistical analysis, machine learning algorithms, and data visualization techniques.
• Experience with machine learning frameworks and libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Familiarity with data manipulation libraries (e.g., Pandas, NumPy) and data visualization tools (e.g., Matplotlib, Seaborn).
• Solid understanding of SQL and database concepts for querying and extracting data.
• Excellent problem-solving skills and the ability to work with complex, unstructured datasets.
• Effective communication skills to explain technical concepts to non-technical stakeholders.
• Experience with big data technologies (e.g., Hadoop, Spark) is a plus.
• Knowledge of cloud platforms and services for data analysis (e.g., AWS, Azure) is advantageous.
• Familiarity with natural language processing (NLP) and text analysis is a plus.
• Advanced degree (Master’s or PhD) in a related field is beneficial but not required.

• Collaborate with business stakeholders to understand their data needs and objectives.
• Collect, clean, and preprocess data from various sources for analysis.
• Perform exploratory data analysis to identify trends, patterns, and correlations.
• Develop and implement predictive models and machine learning algorithms to solve business challenges.
• Apply statistical analysis techniques to analyze complex datasets and draw meaningful conclusions.
• Create data visualizations and reports to communicate insights effectively to non-technical audiences.
• Collaborate with data engineers to optimize data pipelines for efficient data processing.
• Conduct A/B testing and experimentation to evaluate the effectiveness of different strategies.
• Stay up-to-date with advancements in data science, machine learning, and artificial intelligence.
• Assist in the development and deployment of machine learning models into production environments.
• Provide data-driven insights and recommendations to support strategic decision-making.
• Collaborate with other data scientists, analysts, and cross-functional teams to drive data initiatives.