Data Scientist

We are looking for Data Scientists whose roles and responsibilities include extracting data from multiple sources, using machine learning tools to organize data, process, clean, and validate the data, analyzing the data for information and patterns, developing prediction systems, presenting the data clearly, and proposing solutions and strategies.

What sets INVID apart is our collaborative and flexible work environment. We encourage our team to raise the bar in everything they do while maintaining a healthy work-life balance. With our hybrid work model, team members thrive both in the office and remotely. We foster a culture of mutual respect, autonomy, and accountability, where your voice matters and your growth is supported. From structured career paths and paid professional development to access to industry events, we’re committed to your success.

Join us at INVID, where innovation meets support, and together we deliver excellence.

Essential Duties and 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.
• 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.

Experience:

Also, the following experience is required to successfully execute the responsibilities assigned to this position:

• Experience querying databases and using statistical computer languages: R, Python, SLQ.
• Experience using web services: Redshift, S3, Spark, Digital Ocean.
• Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks.
• Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, and Facebook Insights.
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL.
• Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot.
• 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.

Other Qualifications:

• Strong problem-solving skills with an emphasis on product development.
• 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) and experience with applications.
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and master new technologies and techniques.
• Coding knowledge and experience with several languages: C, C++, Java, and JavaScript.
• Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, and social network analysis.
  

Education:

Candidate must hold a master’s degree or a Ph.D. in computer science, information technology, statistics, informatics, data science, mathematics, or another quantitative field. They must also have a minimum of 5-7 years of proven work experience in a Data Scientist role, specifically in the technology industry.

Other:

Must be a U.S. citizen

Must be a U.S. Resident

Fully Bilingual (English and Spanish)

EEO