Wavicle Data Solutions
Data Scientist
Wavicle Data Solutions, California, Missouri, United States, 65018
About the RoleWe are looking for a
Data Scientist
who will perform mission critical duties in our data science consulting practice. A passionate professional who can blend the ever-evolving technology landscape of Cloud and Advanced Analytics with the complex and high-impact space of changing vertical markets.
The
Data Scientist
will be responsible for leading a team of talented consultants to develop, deliver, and maintain cutting edge diagnostic, predictive, prescriptive and AI applications for our client base. This role will be responsible for expanding, optimizing, and monitoring our expanding CI/CD model pipelines through meticulous architecting, cutting edge modelling, intelligent business logic, consistent data governance, testing and continuous delivery.
Responsibilities
Lead and provide advanced analytics expertise for projects that drive optimization of decisions for client(s), within a team of analysts, scientists, and engineers.
Partner with various business units, business analysts, and data stewards to understand the business needs, formulate business problems, and translate those problems into analytical solutions.
Identify data science and advanced analytics use cases that drive business value for clients and implement those use cases by building models, prototyping, executing filed trials, deploying models into production, integrating model scores into decision support and point applications, and managing models (for degradation, population drift, adoption) in production.
Develop custom models and processes to ensure maximum effectiveness of client insights.
Partner with data analysts/engineers and architects to provide solutions leveraging models with statistical analysis tools and data visualization applications.
Obtain and/or maintain technical expertise of available data science tools (Sagemaker, Databricks, Data Science Libraries, etc.) as well as programming languages (Python, Spark, R, etc.).
Develop data science applications in agile, DataOps approach (CI/CD pipelines).
Identify and implement industry use cases in data science and advanced analytics.
Master data wrangling techniques and rapidly create analysis data sets from disparate data sources in a lab environment.
Perform extensive data quality analysis, data profiling, feature engineering and exploratory data analysis on new data sets to determine potential project value.
Work with data engineering teams to ingest data.
Work with internal engineering teams and clients to rapidly ingest data into the lab environment for analysis and after analysis provide data engineers with the benefit of data profiling, quality assessment, wrangling code, and requirements for the purpose of curating data to production.
Modify modeling code to develop production ready scoring engines for developed models.
Generate documentation on existing production models and its influencing business processes, in order to reconcile knowledge gaps between the business, data science, and IT.
Mentor junior data scientists, data wranglers, and data analysts.
Required Knowledge and Level of Experience
4+ years of professional work experience as a Data Scientist or Machine Learning Engineer.
Experience building data science applications in a global team environment using agile methodologies including CI/CD pipelines, DataOps, CRISP-DM, etc. Experience with JIRA, Confluence, and Git.
Experience or certification with Spark, Databricks, GCP is desired.
Natural Language Processing (NLP) or similar analysis (pattern recognition) is desired.
Advanced Analytics techniques including time-series forecasting, optimization, stochastics, game theory, or systems dynamics is desired.
Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms is required.
Python, Pandas, Numpy, Matplotlib, Scikit coding skills are required.
Fluency in a programming language (Python, C, C++, R, Spark, SQL).
Familiarity with Big Data frameworks and visualization tools.
Good understanding of the Cloud (AWS/GCP/Azure) environments.
Effective at telling stories with data using data visualization tools (Tableau, PowerBI, QuickSight, Qlikview, etc.).
Excellent written and verbal communication skills.
Creative drive to try data tools, and explore and discover insights from data.
Bachelor or Master's degree in Engineering, Statistics, Mathematics, Analytics, Operations Research, or other computational field is required.
Open to travel to client locations up to 25%.
#J-18808-Ljbffr
Data Scientist
who will perform mission critical duties in our data science consulting practice. A passionate professional who can blend the ever-evolving technology landscape of Cloud and Advanced Analytics with the complex and high-impact space of changing vertical markets.
The
Data Scientist
will be responsible for leading a team of talented consultants to develop, deliver, and maintain cutting edge diagnostic, predictive, prescriptive and AI applications for our client base. This role will be responsible for expanding, optimizing, and monitoring our expanding CI/CD model pipelines through meticulous architecting, cutting edge modelling, intelligent business logic, consistent data governance, testing and continuous delivery.
Responsibilities
Lead and provide advanced analytics expertise for projects that drive optimization of decisions for client(s), within a team of analysts, scientists, and engineers.
Partner with various business units, business analysts, and data stewards to understand the business needs, formulate business problems, and translate those problems into analytical solutions.
Identify data science and advanced analytics use cases that drive business value for clients and implement those use cases by building models, prototyping, executing filed trials, deploying models into production, integrating model scores into decision support and point applications, and managing models (for degradation, population drift, adoption) in production.
Develop custom models and processes to ensure maximum effectiveness of client insights.
Partner with data analysts/engineers and architects to provide solutions leveraging models with statistical analysis tools and data visualization applications.
Obtain and/or maintain technical expertise of available data science tools (Sagemaker, Databricks, Data Science Libraries, etc.) as well as programming languages (Python, Spark, R, etc.).
Develop data science applications in agile, DataOps approach (CI/CD pipelines).
Identify and implement industry use cases in data science and advanced analytics.
Master data wrangling techniques and rapidly create analysis data sets from disparate data sources in a lab environment.
Perform extensive data quality analysis, data profiling, feature engineering and exploratory data analysis on new data sets to determine potential project value.
Work with data engineering teams to ingest data.
Work with internal engineering teams and clients to rapidly ingest data into the lab environment for analysis and after analysis provide data engineers with the benefit of data profiling, quality assessment, wrangling code, and requirements for the purpose of curating data to production.
Modify modeling code to develop production ready scoring engines for developed models.
Generate documentation on existing production models and its influencing business processes, in order to reconcile knowledge gaps between the business, data science, and IT.
Mentor junior data scientists, data wranglers, and data analysts.
Required Knowledge and Level of Experience
4+ years of professional work experience as a Data Scientist or Machine Learning Engineer.
Experience building data science applications in a global team environment using agile methodologies including CI/CD pipelines, DataOps, CRISP-DM, etc. Experience with JIRA, Confluence, and Git.
Experience or certification with Spark, Databricks, GCP is desired.
Natural Language Processing (NLP) or similar analysis (pattern recognition) is desired.
Advanced Analytics techniques including time-series forecasting, optimization, stochastics, game theory, or systems dynamics is desired.
Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms is required.
Python, Pandas, Numpy, Matplotlib, Scikit coding skills are required.
Fluency in a programming language (Python, C, C++, R, Spark, SQL).
Familiarity with Big Data frameworks and visualization tools.
Good understanding of the Cloud (AWS/GCP/Azure) environments.
Effective at telling stories with data using data visualization tools (Tableau, PowerBI, QuickSight, Qlikview, etc.).
Excellent written and verbal communication skills.
Creative drive to try data tools, and explore and discover insights from data.
Bachelor or Master's degree in Engineering, Statistics, Mathematics, Analytics, Operations Research, or other computational field is required.
Open to travel to client locations up to 25%.
#J-18808-Ljbffr