Data Scientist

1. Data Collection & Cleaning: Gathering large amounts of data from various sources, including structured and unstructured data, and cleaning it to ensure its quality and accuracy.
2. Data Analysis: Using statistical methods and machine learning models to analyze data, identify trends, patterns, and insights that are valuable to the business.
3. Model Development: Building predictive models using algorithms, statistical techniques, and machine learning to forecast outcomes and behaviors.
4. Visualization & Reporting: Creating visual reports or dashboards to communicate findings to stakeholders in a way that's easy to understand, often using tools.
5. Collaboration with Teams: Working closely with business stakeholders, engineers, and other data professionals to understand business challenges and provide data-driven solutions.
6. Research & Development: Staying up-to-date with the latest developments in data science, AI, and machine learning to apply innovative methods to business problems.
7. Programming & Software Skills: Proficient in programming languages such as Python, R, or SQL for data analysis, and familiar with frameworks for machine learning.

Qualifications

• Bachelor's degree or equivalent experience in quantative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
• At least 1 - 2 years' of experience in quantitative analytics or data modeling
• Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms
• Fluency in a programming language (Python, C,C , Java, SQL)
• Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau)