Eon is looking for a Data Scientist who will support our 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. They 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. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes. Don’t hesitate to apply!
Your objectives for this Role:
- Collaborate with engineering and customer’s business team to develop an understanding of needs.
- Research and devise innovative statistical models for data analysis
- Enable smarter business processes and implement analytics for meaningful insights
- Keep current with technology and industry developments in Machine Learning and Data Science
Daily and Monthly Responsibilities:
- Work as the data strategist, identifying and integrating new datasets that can be leveraged through our product capabilities and work closely with the engineering team to strategize and execute the development of data models
- Execute analytical experiments methodically to help solve various problems
- Identify relevant data sources and sets to mine for client business needs, and collect large structured and unstructured datasets and variables
- Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy
- Implement analytical models into production by collaborating with web developers and machine learning engineers.
- Communicate analytic solutions to stakeholders and implement improvements as needed to operational systems
Skills and Languages you will work on:
- Mathematics, and statistical analysis
- Advanced pattern recognition and predictive modeling
- DB’s, Postgres SQL, Document-based DB ( Elastic search)
- Analytics tool like d3js and Kibana, AWS quick sight
- Comfort working in a dynamic, research-oriented group with several ongoing concurrent projects
- 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 Ph.D. 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,
- 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.