Manages the identification and utilization of large data sets to identify trends, patterns, and provide key business insights.
Oversees and promotes data mining, cleaning, and aggregation processes and frameworks to prepare data, implement data models, conduct analysis, and develop databases. Coordinates the design and implementation of big data solutions for an organization, collaborating and liaising with stakeholders to ensure needs are captured. Provides technical guidance to evaluate data models, review code, and source data pipelines. Prioritizes tasks and allocates resources effectively to ensure timely delivery of projects. Builds team capability with mentoring, coaching, and professional development.
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 Science Senior Manager 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-Applying advisory methods to deliver solutions for internal or external clients' technology needs.
Level 1 Behaviors
(General Familiarity)
Lists the basic obstacles, challenges, and potential problems in technology advising.
Level 2 Behaviors
(Light Experience)
Supports management for formulating advising solutions to address basic business issues.
Level 3 Behaviors
(Moderate Experience)
Utilizes technology advising tools to identify and provide interventions for technology issues.
Level 4 Behaviors
(Extensive Experience)
Provides advice for continuous improvement to integrate our technology and improve our processes.
Level 5 Behaviors
(Mastery)
Leads in developing and implementing technology advising tools to optimize functions in our workplace.
There are 0 hard skills for Data Science Senior Manager.
10 general skills for Data Science Senior Manager, Big Data Analytics, Business Intelligence, Data Analytics, etc.
10 soft skills for Data Science Senior Manager, Business Acumen, Technology Advising, Planning and Organizing, etc.
While the list totals 20 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 Science Senior Manager, he or she needs to be skilled in Business Acumen, be skilled in Technology Advising, and be an expert in Planning and Organizing.
