Data Scientist at Mink & Bauman – New York, New York

Most data scientists use the following core technical skills in their daily work:

Statistical analysis: Identify patterns in data. This includes having a keen sense of pattern detection and anomaly detection.
Machine learning: Implement algorithms and statistical models to enable a computer to automatically learn from data.
Computer science: Apply the principles of artificial intelligence, database systems, human/computer interaction, numerical analysis, and software engineering.
Programming: Write computer programs and analyze large datasets to uncover answers to complex problems. Data scientists need to be comfortable writing code and working in a variety of programming languages, such as Java, R, Python, and SQL.
Data storytelling: Communicate actionable insights using data, often for a nontechnical audience.
Data scientists play a key role in helping organizations make sound decisions. As such, they need “soft skills” in the areas listed below.

Business intuition: Connect with stakeholders to gain a full understanding of the problems they’re looking to solve.
Analytical thinking: Find analytical solutions to abstract business issues.
Critical thinking: Apply objective analysis of facts before coming to a conclusion.
Inquisitiveness: Look beyond what’s on the surface to discover patterns and solutions within the data.
Interpersonal skills: Communicate across a diverse audience across all levels of an organization.