Data Scientist

Technical Skills:
Programming Languages: Proficiency in Python (especially for data science, AI Models, Datasets, and Training) is a must.
Machine Learning: Familiarity with machine learning algorithms and their applications in data science is becoming increasingly important.
Mastering Asterisk is a must.
Familiarity with SQL for database querying
Matering Git Version Control
Statistical Knowledge: A solid understanding of statistical concepts like hypothesis testing, regression analysis, and probability is essential.
Data Wrangling: Ability to clean, manipulate, and transform data from various sources to prepare it for analysis.
Data Visualization: Expertise in using tools like Tableau or libraries like matplotlib to create clear and impactful visualizations that communicate insights effectively.
Soft Skills:
Problem-Solving Aptitude: A knack for breaking down complex problems into manageable parts and finding creative solutions through data analysis.
Communication Skills: The ability to translate complex data findings into clear and concise explanations for both technical and non-technical audiences.
Collaboration: Data scientists often work within teams, so the ability to collaborate effectively with engineers, product managers, and other stakeholders is crucial.
Education and Experience:
Minimum 1 Year Experience in a related field.
A Bachelor's degree in a quantitative field like Computer Science, Statistics, or Mathematics is generally preferred.
A Master's degree in Data Science or a related field can be advantageous.
Experience in a data-related role, such as data analyst, is a plus.
The amount of experience required can vary depending on the specific job role and seniority level.