What does a Data Scientist II 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 Ii Salaries

There are no current reports for Data Scientist Ii salaries. You can add additional job titles in your job preferences to see related salary information.

Glassdoor Estimated Salary

Data Scientist II Career Path

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

Data Scientist II
No Salary Reports
Data Scientist IV
No Salary Reports
See Career Path

Data Scientist II Insights

Read what Data Scientist II professionals have to say about their job experiences and view top companies for this 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.”

Data Scientist
20 Apr 2021

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

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”

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”

Lead Data Scientist
27 Sep 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.”

Vice President Data Science
28 May 2021

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

Zions BancorporationZions Bancorporation
Data Scientist
7 Oct 2020

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

See More

Data Scientist II Interviews

Related Careers

Bi Analyst
13% skills overlap
Bi Manager
Data Analyst
25% skills overlap
Bi Engineer
No skills overlap

Data Scientist II jobs

Frequently asked questions about the role and responsibilities of a data scientist ii

When working as a data scientist ii, the most common skills you will need to perform your job and for career success are Statistics, Machine Learning, Python, Datasets and Programming Languages.

The most similar professions to data scientist ii are:
  • Bi Analyst
  • Bi Manager
  • Data Analyst
  • Bi Engineer

The most common qualifications to become a data scientist ii is a minimum of a Bachelor's Degree and an average of 0 - 1 of experience not including years spent in education and/or training.