The Role
Analyze large company datasets to generate business insights for product, sales, marketing and leadership. Build, validate and deploy predictive models and algorithms, design A/B testing frameworks, assess new data sources, create data architectures, and coordinate with cross-functional teams to implement and monitor model performance and outcomes.
Summary Generated by Built In
Data Scientist will support the product, sales, leadership and marketing teams with insights gained from
analyzing company data. The ideal candidate is adept at using large data sets
to find opportunities for product and process optimization and using models to
test the effectiveness of different courses of action.
Must have strong
experience using a variety of data mining/data analysis methods, using a
variety of data tools, building and implementing models, using/creating algorithms
and creating/running simulations. They must have a proven ability to drive
business results with their data-based insights.
Responsibilities for Data Scientist
- 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.
Qualifications for Data Scientist
- 5-7
years of experience manipulating data sets and building statistical models
- Master’s
or PHD in Statistics, Mathematics, Computer Science or another
- 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.
- quantitative
field, and is familiar with the following software/tools:
- Coding
knowledge and experience with several languages: C, C++, Java, JavaScript,
etc.
Skills Required
- 5-7 years manipulating data sets and building statistical models
- Master's or PhD in Statistics, Mathematics, Computer Science or another quantitative field
- Strong problem-solving skills with emphasis on product development
- Experience using statistical computer languages (R, Python, SQL) to manipulate data and draw insights from large data sets
- Experience working with and creating data architectures
- Knowledge of machine learning techniques (clustering, decision tree learning, artificial neural networks) and their trade-offs
- Knowledge of advanced statistical techniques (regression, distributions, statistical tests) and applied experience
- Excellent written and verbal communication skills for cross-team coordination
- Drive to learn and master new technologies and techniques
- Coding knowledge and experience with several languages (C, C++, Java, JavaScript)
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The Company
What We Do
KMR Search Group is an executive search and recruitment firm specializing in the Healthcare, Pharmaceutical, Biotech, and IT Services industries. Operating with a nationwide reach, they help companies identify and place top-tier leadership talent in specialized roles, as seen in their history of conducting high-level searches for positions such as General Managers and Chief Financial Officers across various industrial sectors.
