Success in data science requires a blend of technical, analytical, and interpersonal skills. Here are the key skills needed:

1. Statistical Analysis and Mathematics: A strong foundation in statistics and mathematics is essential for understanding data patterns and building models. Knowledge of probability, statistical tests, distributions, and linear algebra is crucial.
2. Programming Skills: Proficiency in programming languages such as Python, R, and SQL is vital for data manipulation, analysis, and visualization. These languages are used to write algorithms, clean data, and perform complex calculations.
3. Data Wrangling and Cleaning: The ability to clean and preprocess raw data is critical. Data scientists spend a significant amount of time preparing data for analysis, dealing with missing values, and ensuring data quality.
4. Machine Learning: Understanding machine learning algorithms and techniques is crucial for building predictive models. This includes knowledge of supervised and unsupervised learning, neural networks, and natural language processing.
5. Data Visualization: The ability to create compelling visualizations using tools like Tableau, Matplotlib, or Seaborn helps in communicating findings effectively to stakeholders.
6. Domain Knowledge: Understanding the industry or field where you are applying data science is important for contextualizing data and making relevant insights.
7. Problem-Solving Skills: Critical thinking and problem-solving skills are necessary for identifying the right questions to ask and the best methods to find answers.
8. Communication Skills: Data scientists must be able to explain complex technical results to non-technical stakeholders clearly and concisely.
9. Curiosity and Continuous Learning: The field of data science is constantly evolving, so a passion for learning and staying updated with the latest trends and technologies is important.

Mastering these skills enables data scientists to effectively analyze data, build models, and derive actionable insights that drive decision-making​