AI Data science

HP•Houston, TX

About The Position

This role is responsible for analyzing and interpreting complex data sets using statistical techniques to identify trends, patterns, and insights that can be used to form business decisions and improve organizational performance. The role designs and develops methods, processes, and systems to consolidate and analyze unstructured, diverse big data sources to generate actionable insights and solutions. The role develops programs, algorithms, and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.

Requirements

Four-year or Graduate Degree in Mathematics, Statistics, Economics, Computer Science, Data Science, or any other related discipline or commensurate work experience or demonstrated competence.
4-7 years of work experience, preferably in data analytics, statistical modeling, machine learning, or a related field or an advanced degree with 3-5 years of work experience.
Algorithms
Amazon Web Services
Apache Spark
Artificial Intelligence
Big Data
Computer Science
Data Analysis
Data Mining
Data Science
Data Visualization
Deep Learning
Machine Learning
Natural Language Processing
Predictive Modeling
Python (Programming Language)
R (Programming Language)
SQL (Programming Language)
Statistical Modeling
Statistics
Tableau (Business Intelligence Software)
Effective Communication
Results Orientation
Learning Agility
Digital Fluency
Customer Centricity

Nice To Haves

Programming Language/s Certification (SQL, Python, or similar)

Responsibilities

Oversees data mining using modern tools and programming languages.
Develops predictive and prescriptive models of moderate complexity to surface insights; drives action, defines success measures and tracks performance of models.
Drives the implementation of models to uncover patterns and predictions creating business value and innovation.
Partners with data engineering teams across multiple business lines to build data pipelines, improve data assets, quality, metrics, and insights.
Creates visualizations and other forms of communication that effectively showcase insights and findings to both technical and non-technical audiences.
Leads a project team of data science professionals and provides guidance, training and mentoring to less experienced staff members.
Collaborates and communicates with project team regarding project progress and issue resolution.
Represents the data science team for all phases of larger and more-complex development projects.
Identifies and recommends improvement upon existing methodologies by developing new data sources, testing model assumptions, and fine-tuning model parameters.
Maintains proficiency within the data science domain by keeping up with technology and trend shifts.