Data Scientist

Lexical Intelligence, LLC•Bethesda, MD

1d•$90,000 - $95,000•Onsite

About The Position

Lexical Intelligence, LLC, seeks a Data Scientist in Rockville MD to serve as a technical advisor and support analytics needs; understand emerging technologies and demonstrate the ability to analyze and solve problems; partner with business analytics to frame and translate business needs into appropriate research questions for the team; collaborate with the team to provide strategic assessments of methods and technologies related to development and design standard operating procedures; use Python and alternate programming languages, such as Java and SQL, to mine complex dataset from different varieties of sources and platforms; manage data pipelines, develop data tables, create relevant scripts and code for analytical purposes; execute models and apply statistical tools to perform data analysis; develop well-managed data solutions to automate the frameworks of business logic/rules for data analysis; build Dashboards to demonstrate results and data findings for clients/customers; partner with the business analysts to provide consultancy and translate the business needs to design and develop tools, techniques, metrics, and dashboards for insights and data visualization; work directly with end users and managers to procure business requirements and translate into technology work instructions; drive analysis that provides meaningful insights on business strategies; drive an understanding and adherence to the principles of data quality management including metadata, lineage, and business definitions; work collaboratively with appropriate tech teams to build database and data access governance; collaborate, create and organize database in Azure SQL, provide a single Python API to update and optimize the efficiency of data query; draft documentation to monitor and report on data management and data quality; build pipelines for data exploration and visualize workforce data in Python; use Principal Component Analysis (PCA) for dimensionality reduction; use K-means clustering and Hierarchical clustering to discover conceptually meaningful classes of object; use NumPy, Pandas, Matplotlib, Seaborn, Plotly, Scikit-Learn libraries to visualize data trends and export template deliverables; build an interactive dashboard by Streamlit library for Demonstration.

Requirements

Bachelor’s degree in Data Analytics, a related field, or a foreign equivalent.
Work experience, coursework experience, or university experience utilizing Python.
Work experience, coursework experience, or university experience utilizing Java.
Work experience, coursework experience, or university experience utilizing PostgresSQL.
Work experience, coursework experience, or university experience utilizing Power BI Dashboard.
Work experience, coursework experience, or university experience utilizing Qlik.
Work experience, coursework experience, or university experience using data and algorithms to enable artificial intelligence (AI) to gradually improve its accuracy.
Work experience, coursework experience, or university experience utilizing Data Mining to explore data and extract insights.
Work experience, coursework experience, or university experience utilizing Natural Language Processing (NLP).
Work experience, coursework experience, or university experience utilizing Data Analytics/Data Science.
Work experience, coursework experience, or university experience translating data requirements into Conceptual Design.
Work experience, coursework experience, or university experience building pipelines to organize/process the data.
Work experience, coursework experience, or university experience utilizing database architecture.
Work experience, coursework experience, or university experience utilizing Data Visualization.
Work experience, coursework experience, or university experience utilizing Programming/Software development.
Work experience, coursework experience, or university experience utilizing Statistics.
Work experience, coursework experience, or university experience utilizing Predictive Analysis.

Nice To Haves

Serve as a technical advisor and support analytics needs.
Understand emerging technologies and demonstrate the ability to analyze and solve problems.
Partner with business analytics to frame and translate business needs into appropriate research questions.
Collaborate with the team to provide strategic assessments of methods and technologies related to development and design standard operating procedures.
Use Python and alternate programming languages, such as Java and SQL, to mine complex dataset from different varieties of sources and platforms.
Manage data pipelines, develop data tables, create relevant scripts and code for analytical purposes.
Execute models and apply statistical tools to perform data analysis.
Develop well-managed data solutions to automate the frameworks of business logic/rules for data analysis.
Build Dashboards to demonstrate results and data findings for clients/customers.
Partner with the business analysts to provide consultancy and translate the business needs to design and develop tools, techniques, metrics, and dashboards for insights and data visualization.
Work directly with end users and managers to procure business requirements and translate into technology work instructions.
Drive analysis that provides meaningful insights on business strategies.
Drive an understanding and adherence to the principles of data quality management including metadata, lineage, and business definitions.
Work collaboratively with appropriate tech teams to build database and data access governance.
Collaborate, create and organize database in Azure SQL, provide a single Python API to update and optimize the efficiency of data query.
Draft documentation to monitor and report on data management and data quality.
Build pipelines for data exploration and visualize workforce data in Python.
Use Principal Component Analysis (PCA) for dimensionality reduction.
Use K-means clustering and Hierarchical clustering to discover conceptually meaningful classes of object.
Use NumPy, Pandas, Matplotlib, Seaborn, Plotly, Scikit-Learn libraries to visualize data trends and export template deliverables.
Build an interactive dashboard by Streamlit library for Demonstration.
Utilize the following technologies: Python, Java, PostgreSQL, Excel and Microsoft Office Suites, Power BI (dashboard), Qlik (dashboard), Natural Language Processing (NLP), Data Analytics/Data Science, Database, Data Visualization, Programming/software development, Statistics, Predictive Analysis.

Responsibilities

Serve as a technical advisor and support analytics needs.
Understand emerging technologies and demonstrate the ability to analyze and solve problems.
Partner with business analytics to frame and translate business needs into appropriate research questions.
Collaborate with the team to provide strategic assessments of methods and technologies related to development and design standard operating procedures.
Use Python and alternate programming languages, such as Java and SQL, to mine complex datasets from different varieties of sources and platforms.
Manage data pipelines, develop data tables, create relevant scripts and code for analytical purposes.
Execute models and apply statistical tools to perform data analysis.
Develop well-managed data solutions to automate the frameworks of business logic/rules for data analysis.
Build Dashboards to demonstrate results and data findings for clients/customers.
Partner with business analysts to provide consultancy and translate business needs into design and development of tools, techniques, metrics, and dashboards for insights and data visualization.
Work directly with end users and managers to procure business requirements and translate into technology work instructions.
Drive analysis that provides meaningful insights on business strategies.
Drive an understanding and adherence to the principles of data quality management including metadata, lineage, and business definitions.
Work collaboratively with appropriate tech teams to build database and data access governance.
Collaborate, create and organize database in Azure SQL, provide a single Python API to update and optimize the efficiency of data query.
Draft documentation to monitor and report on data management and data quality.
Build pipelines for data exploration and visualize workforce data in Python.
Use Principal Component Analysis (PCA) for dimensionality reduction.
Use K-means clustering and Hierarchical clustering to discover conceptually meaningful classes of object.
Use NumPy, Pandas, Matplotlib, Seaborn, Plotly, Scikit-Learn libraries to visualize data trends and export template deliverables.
Build an interactive dashboard by Streamlit library for Demonstration.