What does a Data Scientist, Analytics 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.

  • 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.
  • 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.
EducationBachelor's Degree
Work/Life Balance
4.0 ★
Salary Range--
Career Opportunity
3.9 ★
Avg. Experience2-4 years

Data Scientist, Analytics Salaries

Average Base Pay

$130,044 /yr
Same as national average
Not including cash compensation
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$98K
Median: $130K
$172K
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Glassdoor Estimated Salary

Data Scientist, Analytics Career Path

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

L2
Data Scientist
$117,212/yr
L3
L4
See Career Path

Data Scientist, Analytics Insights

Read what Data Scientist, Analytics professionals have to say about their job experiences and view top companies for this career.
Carpenter TechnologyCarpenter Technology
Senior Data Scientist
May 28, 2021

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

IntellibondsIntellibonds
Data Scientist
Apr 20, 2021

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

84.51°84.51°
Lead Data Scientist
Sep 27, 2021

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

Mu SigmaMu Sigma
Trainee Decision Scientist
Apr 6, 2021

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

Zions BancorporationZions Bancorporation
Data Scientist
Oct 7, 2020

“This is a good place once you want your career to coast and build your 401k and HSA.”

DataikuDataiku
Vice President Data Science
May 28, 2021

“I’ve been promoted twice during my time here and continue to have great personal and career growth.”

SiemensSiemens
Data Scientist
Sep 13, 2021

“For data roles does not pay so well and lacks a structured career development program.”

AI CorporationAI Corporation
Data Scientist
Apr 8, 2021

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

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Data Scientist, Analytics Interviews

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