Data Scientist - Houston, United States - Oreva Technologies

Description

Position: Data Scientist/GIS

Location: Houston, TX (Hybrid - 3 days on-site, 2 days remote)

Duration: 6-month contract (most likely will continue extending)

Reason for Need: Build out of new group - they have 8 models/optimizers between the two teams ranging from reliability, resiliency, load and risk forecasting

Project Details: Build data products and solutions to complex and advanced data problems faced throughout the organization. Partner with various business clients, data engineers, and data analysts to ensure your stakeholders have the advanced analytics support they need. Areas of focus include classification, regression, natural language processing, forecasting, change point detection, sentiment analytics, etc. Expected to collaborate with business SMEs and communicate results to a non-technical audience

Must Have Skills:

Data Scientist/GIS

• Minimum of (5) years of experience working as a data scientist or in a related field
• Experience with ArcGIS Pro toolkits (i.e. Spatial Analyst, Spatial Statistics, Network Analyst)
• 5+ years' experience with ArcGIS or other geospatial tools
• Experience with SQL, and relational or schema-less (NoSQL) databases
• Experience with programming languages: Python, R, MATLAB, etc.
• Experience with data visualization tools: Tableau, PowerBI, Looker, etc.
• Experience with cloud technologies: Google Cloud Platform, AWS, Azure, or similar technologies
• Experience applying statistical or machine learning algorithms, econometrics, and/or predictive modeling
• Strong analytical and critical thinking skills

Soft Skills:

• Ability to speak with all different stakeholders / business units

Nice to Have Skills:

• Project Management Experience
• Utility Experience
• Experience with data governance

Education/Certification Requirements:

• Bachelor's Degree in quantitative discipline: Statistics, Mathematics, Economics, Information Systems, or related field

Day to Day Responsibilities:

• Apply advanced analytics methods to address business problems.
• Develop, tune, and deploy statistics & machine learning models including but not limited to classification, regression, natural language processing, forecasting, change point detection, sentiment analytics, etc.
• Use version control and GIT principles to collaborate and maintain a codebase alongside peers.
• Use basic MLOps principles to deploy and monitor models in production environments.
• Work within Google Cloud Platform (GCP) to design and manage components of a data product or service.
• Perform exploratory data analysis that supports or justifies hypothesis about data-related questions.
• Partner with business units to define data problems, measurable success criteria, and actionable deliverables.
• Leverage data visualization tools to create compelling stories about insights you find and discover.
• Design and build experiments to measure the success from the models in production.
• Communicate insights, updates, and outcomes in a way that is understood by non-technical stakeholders.
• Use data engineering techniques to identify required data sources, wrangling data, engineering new features, and related techniques.
• Collaborate with cross-functional teams to identify opportunities for process optimization, cost reduction, and revenue generation using data-driven insights