What does a Senior Data Scientist Manager do?

Data scientists utilize their analytical, statistical, and programming skills to collect, analyze, and interpret large data sets. They then use this information to develop data-driven solutions to difficult business challenges. Data scientists commonly have a bachelor's degree in statistics, math, computer science, or economics. Data scientists have a wide range of technical competencies including: statistics and machine learning, coding languages, databases, machine learning, and reporting technologies.

What responsibilities are common for Senior Data Scientist Manager jobs?
  • Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
  • Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
  • Assess the effectiveness and accuracy of new data sources and data gathering techniques.
  • Develop custom data models and algorithms to apply to data sets.
  • Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
  • Develop company A/B testing framework and test model quality.
  • Coordinate with different functional teams to implement models and monitor outcomes.
  • Develop processes and tools to monitor and analyze model performance and data accuracy.
What are the typical qualifications for Senior Data Scientist Manager jobs?
  • Strong problem solving skills with an emphasis on product development.
  • Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
  • Experience working with and creating data architectures.
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
  • Excellent written and verbal communication skills for coordinating across teams.
  • A drive to learn and master new technologies and techniques.
  • We’re looking for someone with 5-7 years of experience manipulating data sets and building statistical models, has a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools:
    • Coding knowledge and experience with several languages: C, C++, Java,
    • JavaScript, etc.
    • Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
    • Experience querying databases and using statistical computer languages: R, Python, SLQ, etc.
    • Experience using web services: Redshift, S3, Spark, DigitalOcean, etc.
    • Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
    • Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
    • Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
    • Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.
EducationGraduate Degree
Work/Life Balance
4.0 ★
Salary Range--
Career Opportunity
3.9 ★
Avg. Experience5-7 years

Senior Manager Of Data Scientist Salaries

Glassdoor Estimated Salary

Senior Data Scientist Manager Career Path

Learn how to become a Senior Data Scientist Manager, what skills and education you need to succeed, and what level of pay to expect at each step on your career path.

L4
Senior Manager of Data Science
No Salary Reports
L5
Principal Data Scientist
No Salary Reports
L4

Average Years of Experience

0 - 1
0%
2 - 4
15%
5 - 7
72%
8+
13%
Not including years spent in education and/or training
See Career Path

Senior Data Scientist Manager Insights

Read what Senior Data Scientist Manager professionals have to say about their job experiences and view top companies for this career.
IntellibondsIntellibonds
Data Scientist
20 Apr 2021

“Excellent leadership and a motivated team make Intellibonds a fantastic firm from which to advance a career.”

Carpenter TechnologyCarpenter Technology
Senior Data Scientist
28 May 2021

“The domain is incredibly fascinating and the chance to work with metallurgists is really awesome.”

AttestAttest
Junior Data Scientist
24 Mar 2021

“I really enjoyed the opportunity to experiment and try new/state of the art techniques in the DS team”

IntuitIntuit
Senior Data Scientist
19 Oct 2020

“Management really makes an effort to make sure you develop your career and skills in the way that you want”

84.51°84.51°
Lead Data Scientist
27 Sept 2021

“There are quite a few reviews saying promotions are political and I just don't see that.”

Mu SigmaMu Sigma
Trainee Decision Scientist
6 Apr 2021

“Cafeteria didn't provide great range in cuisines and passes the hygiene test just above average.”

Ravelin Technology Ravelin Technology
Data Scientist
12 Mar 2021

“Great salary and I've had multiple pay rises when I didn't expect them.”

AI CorporationAI Corporation
Data Scientist
8 Apr 2021

“I firstly joined as an Alert Management Analyst and was offered good career progression opportunities.”

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Senior Data Scientist Manager Interviews

Frequently asked questions about the role and responsibilities of data scientists

Data scientists combine math, computer science, analytics, and business acumen to interpret large amounts of data to help businesses devise future strategies. They determine how the data can be used to achieve a company's targets.

Data science is a great career. More and more organizations are employing data scientists to use data analysis to create online frameworks, implement machine learning techniques, and stay at the forefront of data science innovation.

Data science is a challenging job. Analyzing vast amounts of data and coming up with solutions to better organizations can put a great deal of pressure on these individuals. However, the rewarding nature of this career makes it worthwhile to work as a data scientist.

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