Senior Data Scientist

Day to day responsibilities

• 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.
• Cook up with different functional teams to implement models and monitor outcomes.
• Develop processes and tools to monitor and analyze model performance and data accuracy.

Skills needed to be successful in this role

• Strong problem-solving skills with an emphasis on product development.
• Experience using statistical computer languages (R, Python, SQL, 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.

Additional Requirements for the role

• 5-7 years of experience manipulating data sets and building statistical models.
• A Master’s degree or PHD in Statistics, Mathematics, Computer Science or another quantitative field.
• Familiarity with the following software/tools:
• Experience querying databases and using statistical computer languages: R, Python, SQL, 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, Adobe Analytics
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark
• Experience visualizing/presenting data

Pay

Competitive salaries and benefits, including health, dental, vision, life, short and long-term disability insurance, and a 401(k) retirement plan with company match.