As a Data Scientist, you will be responsible for analyzing data to solve complex problems and help the organization make data-driven decisions. You will develop models that predict trends and patterns, optimize processes, and help improve business performance.

Detailed Responsibilities:

• Analyze and interpret large and complex datasets to identify patterns, trends, and insights.
• Build predictive models and machine learning algorithms to solve business problems.
• Collaborate with business stakeholders to understand their requirements and translate them into data-driven solutions.
• Use statistical techniques to validate hypotheses and assess the performance of models.
• Design experiments and perform A/B testing to measure the impact of changes and make recommendations.
• Develop data pipelines and automated workflows to ensure data availability and reliability for analysis.
• Create data visualizations and reports to communicate findings and recommendations to non-technical stakeholders.
• Continuously monitor and improve the accuracy of predictive models and analytics solutions.
• Stay updated with the latest industry trends, tools, and techniques in data science and analytics.
• Work with engineering teams to deploy machine learning models into production environments.
• Collaborate with data engineers to ensure data quality and efficient data management.

Skills & Expertise:

• Proficiency in programming languages such as Python, R, or Java for data analysis and modeling.
• Strong experience with machine learning algorithms (e.g., decision trees, random forests, neural networks, clustering, regression).
• Expertise in statistical analysis and predictive modeling.
• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib).
• Familiarity with big data tools and technologies (e.g., Hadoop, Spark, SQL).
• Strong understanding of data structures, data cleaning, and data transformation techniques.
• Knowledge of cloud platforms (e.g., AWS, Google Cloud, Azure) is an advantage.
• Excellent problem-solving and analytical skills.
• Ability to communicate complex technical concepts to non-technical stakeholders.
• Strong understanding of business operations and how data can improve business outcomes.

Preferred Qualifications:

• Experience working with deep learning frameworks (e.g., TensorFlow, PyTorch).
• Knowledge of natural language processing (NLP) and computer vision techniques.
• Experience with big data and distributed computing systems.
• Prior experience working in industries such as finance, healthcare, or technology is a plus.