Plays a crucial role in helping businesses make informed decisions by leveraging data & will collaborate with stakeholders, design data models, create algorithms, and share meaningful insights to drive business success
Key Responsibilities.
Work with supply chain, manufacturing, Sales managers, customer account managers and quality function to produce algorithms. Gathering and interpreting data from various sources.
Cleaning and verifying the accuracy of data sets to ensure data integrity.
Developing and implementing data collection systems and strategies to optimize efficiency and accuracy.
Applying statistical techniques to analyze and interpret complex data sets.
Develop and implement statistical models for predictive analysis.
Build and deploy machine learning models to solve business problems.
Creating visual representations of data through charts, graphs, and dashboards to communicate findings effectively.
Develop dashboards and reports for ongoing monitoring and analysis.
Create, modify and improve complex manufacturing schedule.
Create scenario planning model for manufacturing.
Develop manufacturing schedule adherence probability model.
Regularly monitoring and evaluating data quality, making recommendations for improvements as necessary.
Staying up-to-date with industry trends and best practices in data analysis and reporting.
Ensuring compliance with data privacy and security regulations
Person Profile .
Qualification - B.E/B.Tech
Experience 4-5 Yrs experience in Chemical/ Manufacturing Industry.
Must Have -
Proficiency in data analysis tools such as Microsoft Excel, SQL, and statistical software (e.g., R or Python).
Proficiency in programming languages such as Python or R.
Expertise in statistical analysis, machine learning algorithms, and data manipulation.
Strong analytical and problem-solving skills with the ability to handle complex data sets.
Excellent attention to detail and a high level of accuracy in data analysis.
Solid knowledge of data visualization techniques and experience using visualization tools like Tableau or Power BI.
Strong communication skills to present findings and insights to non-technical stakeholders effectively
Knowledge of statistical methodologies and techniques, including regression analysis, clustering, and hypothesis testing.
Familiarity with data modeling and database management concepts.
Experience in manipulating and cleansing large data sets.
Ability to work collaboratively in a team environment and adapt to changing priorities.
Experience with big data technologies (e.g., Hadoop, Spark).
Knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud).
Familiarity with data engineering and database technologies.