Collects, analyzes, and interprets large data sets to identify trends, patterns, and provide key business insights.
Performs data mining, cleaning, and aggregation processes to prepare data, implement data models, conduct analysis, and develop databases. Develops insights and reports from multiple structured and unstructured data sources using programming, statistical, and analytical techniques and tools. Maintains continuous collaboration with teams to understand the underlying purpose, focus, and objective of each data analysis project to ensure alignment and support. Designs, develops, and implements the most valuable data-driven solutions for the organization.
Salary.com identifies five increasing levels of proficiency for each skill/competency. Some jobs require only a relatively low level of proficiency in each skill/competency, while other jobs will require a more advanced level of proficiency in the same skill/competency. These levels rate the degree of proficiency (skill level, expertise) we expect the incumbent to perform in the given skill/competency for the given job. Note that we intentionally do not associate timeframes or years of experience in performing the skill/competency because that can be misleading. Proficiency levels identify what the incumbent knows and can do rather than how long they have been doing it. Also, note that the proficiency levels are cumulative, e.g., a level 4 proficiency implies the ability to perform all the behaviors at the lower levels.
Check each Data Scientist II skill and competencie below to view definitions.
Skill definition-Collecting, analyzing, and interpreting a large amount of data to uncover information to help organizations make informed business decisions.
Level 1 Behaviors
(General Familiarity)
Lists commonly used analytic tools, techniques, and methods.
Level 2 Behaviors
(Light Experience)
Supports in-memory processing to boost the performance of big data analytic applications.
Level 3 Behaviors
(Moderate Experience)
Utilizes big data analytics tools for data retrieval, preparation, and modeling.
Level 4 Behaviors
(Extensive Experience)
Provides expert analysis and recommendations on current and emerging approaches for big data analytics.
Level 5 Behaviors
(Mastery)
Oversees the big data analytics pipeline development to optimize the entire process.
Skill definition-Evaluating business data, translating it to actionable insights, and using it to make better-informed decisions.
Level 1 Behaviors
(General Familiarity)
Lists the basic features of general business intelligence systems and database structure.
Level 2 Behaviors
(Light Experience)
Supports end-users in using business intelligence tools to query databases for outputs and data preparation.
Level 3 Behaviors
(Moderate Experience)
Utilizes business intelligence platforms to derive insights to present the data to our business.
Level 4 Behaviors
(Extensive Experience)
Provides technical oversight and design to support the development of business intelligence solutions.
Level 5 Behaviors
(Mastery)
Leads the development of visual business intelligence models to utilize business intelligence tools.
Skill definition-Insight into our organization's business, goals, and values. Ability to design and implement initiatives that facilitate successful outcomes.
Level 1 Behaviors
(General Familiarity)
Names our key stakeholders from a business value chain perspective.
Level 2 Behaviors
(Light Experience)
Supports the planning, implementation, and management of training programs that foster process improvements.
Level 3 Behaviors
(Moderate Experience)
Participates in the redesign of organizational structures to reflect business priorities.
Level 4 Behaviors
(Extensive Experience)
Trains others on various business and operation topics.
Level 5 Behaviors
(Mastery)
Forecasts the short-term and long-term impact of various business cases on P&L performance.
Skill definition-Gathering, analyzing, and predicting patterns and structures of historical data and trends to make strategic decisions for better future outcomes.
Level 1 Behaviors
(General Familiarity)
Lists various kinds of applications that use predictive analytics.
Level 2 Behaviors
(Light Experience)
Interprets the reasons for statistical errors, misinterpretations, and false positives.
Level 3 Behaviors
(Moderate Experience)
Works with teams in using different kinds of cross-validation to test results of predictive models.
Level 4 Behaviors
(Extensive Experience)
Researches and lists the cases that are predicted wrongly and then learns how to improve.
Level 5 Behaviors
(Mastery)
Stays current with the latest research on predictive analytics.
There are 0 hard skills for Data Scientist II.
18 general skills for Data Scientist II, Big Data Analytics, Business Intelligence, Data Analytics, etc.
6 soft skills for Data Scientist II, Business Acumen, Predictive Analytics, Critical Thinking, etc.
While the list totals 24 distinct skills, it's important to note that not all are required to be mastered to the same degree. Some skills may only need a basic understanding, whereas others demand a higher level of expertise.
For instance, as a Data Scientist II, he or she needs to be proficient in Business Acumen, be proficient in Predictive Analytics, and be skilled in Critical Thinking.
