Senior Data Science Consultant - Houston
Our Data and Analytics Practice helps our clients strategize, design, build and operate data and analytical platforms through our high-performance teams of data engineers, architects, scientists and analytical leaders. We shape the future of what data-driven organizations look like by driving processes for extracting and using data in creative ways while creating new lines of thinking with our clients under diverse situations.
AIM Consulting is looking for Senior Data Science Consultants with 5-7 years of experience manipulating data sets and building statistical models within the oil and gas industry and holds an advanced degree in Statistics, Mathematics, Computer Science or another quantitative field.
Day-to-day, you will:
- Work with client stakeholders throughout to identify opportunities for leveraging client data to drive business solutions
- Mine and analyze data from client data sources to drive optimization and improvement of business decisions
- Assess the effectiveness and accuracy of new data sources and data gathering techniques (ETL)
- Develop custom data models and algorithms to apply to data sets for our clients
- Use predictive modeling for forecasting, production analysis, preventative maintenance, risk mitigation, revenue generation, and other business outcomes
- Develop processes, tools, and dashboards to monitor and analyze model performance and data accuracy
You have strong problem-solving skills with an emphasis on product development, experience working with and creating data architectures and have excellent written and verbal communication skills for coordinating across teams. You have experience with oil and gas related data and associated stakeholders; and exhibit a passion to master new technologies and modern architecture techniques.
Your knowledge and skillset likely include the following:
- Statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets
- Experience using web services: Redshift, S3, Databricks, Data Factory, Elastic, Snowflake, etc.
- Understanding of distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, etc.
- Experience analyzing data from 3rd party providers and utilizing APIs: Google Analytics, Site Catalyst, Digital Analytics, HIS Markit, Facebook Insights, etc.
- Experience with graphical or spatial data: ESRI, Google Maps, CartoDB
- Machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
- Advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications
- Statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
- Experience visualizing/presenting data for stakeholders using: PowerBI, Spotfire, Business Objects, Jaspersoft, Qlik, Tableau, etc.
- Experience building data pipelines and utilizing ETL tools: SSIS, Informatica, Talend, SAP Data Services, etc.