Data Analyst at Bentley Systems

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Date: Aug 7, 2024
Location: Pune, IN
Company: Bentley Systems

Position Summary:

The Data Analyst is responsible for exploring, cleaning, and preparing the data for the data mining project. They perform descriptive and exploratory data analysis, such as summarizing, visualizing, and profiling the data, and identify any anomalies, outliers, or missing values. They also apply various data mining techniques, such as clustering, classification, association, and regression, to discover patterns and insights from the data. The data analyst needs to have a strong background in statistics, mathematics, and data analysis tools and methods, such as R, SAS, Excel, and Tableau.


Data Analyst Responsibilities: Managing master data, including creation, updates, and deletion. Provide quality assurance of imported data, working with quality assurance analysts if necessary. Commissioning and decommissioning of data sets. Helping develop reports and analyses. Managing and designing the reporting environment, including data sources, security, and metadata. Supporting the data warehouse in identifying and revising reporting requirements. Supporting initiatives for data integrity and normalization. Assessing tests and implementing new or upgraded software and assisting with strategic decisions on new systems.
Generating reports from single or multiple systems. Troubleshooting the reporting database environment and reports. Evaluating changes and updates to source production systems. Training end-users on new reports and dashboards.
Providing technical expertise in data storage structures, data mining, and data cleansing.

 

Data Analyst Requirements: Bachelor’s degree from an accredited university or             college in computer science or relevant training and/or experience.
    7+ years of work experience as a data analyst or in a related field.
    Ability to work with stakeholders to assess potential risks.
    Ability to analyze existing tools and databases and provide software solution             recommendations.
    Ability to translate business requirements into nontechnical, lay terms.
    High-level experience in methodologies and processes for managing large-scale        databases.
    Demonstrated experience in handling large data sets and relational databases.
    Understanding of addressing and metadata standards.
    High-level written and verbal communication skills.

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