W. R. Grace Hiring Drive 2024: W. R. Grace Hiring Drive 2024 for its Data Analyst. W. R. Grace Drive organizes off-campus drives for candidates in any batch. To apply, candidates should have a B.E/B.Tech/M.Tech in Chemical Engineering with a demonstrated interest in Data Analytics. if you are interested, please apply as soon as possible.
Company Name: W. R. Grace
Role: Data Analyst
Location: Chennai
Experience: 1 year
Qualification: B.E/B.Tech/M.Tech in Chemical Engineering with a demonstrated interest in Data Analytics
Batch: Any
Job Type: Full Time
Salary: Best in Industry
W. R. Grace Hiring Drive 2024
Job Description:
- Data Analyst will be part of the India Digital Operations Center and will be responsible for developing organization wide solutions that enables extraction of Insights from Data.
- This includes Integration of data from various Data sources across organization functions, develop data Models using different state of the art ETL tools, develop visualization using BI tools for KPIs enabling data driven decision making.
- Critical to success will also be requirements for the person to recommend ways to improve quality, reliability, and efficiency of the Grace.
Requirements:
- B.E/B.Tech/M.Tech in Chemical Engineering with a demonstrated interest in Data Analytics, or B.E/B.Tech in Computer Science with a minimum of 1 year of prior experience in the Chemical/Manufacturing/Process industry.
- Strong written and verbal communication skills
- Strong analytical and problem-solving skills.
- Strong interpersonal skills needed to manage and collaborate with multiple internal resources within the Grace organization and external resources, including management of vendor relationships.
- Outstanding analytical skills including financial business case creation.
- Ability to quickly learn details of Grace’s chemical processes and identify the impact of automation improvements on the cost, quality, and safety of the manufacturing operation.
- Practical experience in data mining, techniques for data cleaning, transformation, acquisition, preparation, and validation.
- Strong knowledge and practical experience in handling large volume datasets using any programming languages such as Python, SQL, and other scripting languages.
- Comprehensive Understanding/expertise of databases and relational database management systems (RDBMS), particularly skilled at SQL querying for efficient data retrieval, management, and analysis.
- Capacity to analyze and interpret massive datasets, extracting meaningful insights and identifying valuable trends and patterns.
- Demonstrated experience in creating powerful visualizations using BI tools, such as Tableau/Power BI/ SAC to effectively communicate insights and facilitate data-driven decision-making.
- Proficiency in advanced Excel functionalities, including PivotTables, VLOOKUP, and complex data manipulation techniques for insightful data analysis and visualization.
- Demonstrated expertise in advanced analytics and statistical modeling during academic or post academics projects.
- Experience in communicating insights clearly and persuasively to diverse stakeholders
- Experience or Familiarity with cloud environments, especially data lake and data warehousing concepts, with a preference for Google Cloud experience.
- Strong grasp of advanced statistical techniques such as Decision Trees, regression, and correlation.
- Experience implementing AI/ML/DL models using Python and libraries like Pandas, NumPy, Scikit-learn.
- Hands-on experience with handling time series data and time series forecasting.
- Exposure to SAP Modules and maintenance process improvement KPIs
Responsibility:
- Understand business use of data and stakeholder requirements to support work processes and strategic business objectives.
- Leverage data, software engineering, and data science techniques to create business value through data accessibility.
- Develop data-driven decisions and insights using predictive models to support grace operations & monitor the performance of assets as a function of parametric adjustment for manufacture excellence.
- Analyze large volumes of internal and external data using common data science tools (Python, SQL/NoSQL etc.) & various ML Models to deliver valuable insights for operational excellence.
- Effectively summarize & communicate complex analytic results to a variety of audiences
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