Data Analyst - Assistant Manager

Role & responsibilities

Data Management and Analysis:

• Collect, clean, and validate data from various sources, including SAP, KM (Knowledge Management) tools, and IoT systems.
• Perform statistical analyses and create visualizations to identify trends, patterns, and actionable insights.
• Manage and analyses datasets related to inventory, production, and operational performance, ensuring accuracy and reliability.

Reporting and Dashboards:

• Develop and maintain dashboards using tools like Power BI, Tableau, and KM systems to track KPIs.
• Automate recurring reports and provide ad-hoc analytics support to various departments.
• Collaborate with stakeholders to deliver customized reports and insights for decision-making.

Advanced Analytics and Insights:

• Conduct predictive and prescriptive analyses to forecast trends and optimize processes.
• Leverage machine learning models and statistical methods to address operational challenges.
• Perform root cause analysis for anomalies and recommend actionable solutions.

Process Improvement:

• Oversee data integration from DCS, PLC, and IoT devices into centralized systems like Historian and KM.
• Drive data quality initiatives and streamline data workflows to improve reporting accuracy.
• Support the adoption of digital transformation projects, including inventory optimization and energy efficiency analysis.

Collaboration and Training:

• Work closely with cross-functional teams, including operations, engineering, and finance, to align data strategies with business goals.
• Provide training and support to users on data interpretation, dashboard usage, and analytics tools.

Required Qualifications and Skills:

• Education:

  Bachelors degree in Engineering (Mechanical), Data Analytics, Statistics, or related field.

• Experience:

  2-4 years in data analytics, preferably in manufacturing, FMCG, or industrial domains.

• Technical Skills:

• Proficient in Excel, SQL, Python/R, and data visualization tools (Power BI, Tableau).
• Familiarity with SAP modules, KM dashboards, and IoT data sources.
• Knowledge of predictive modeling, statistical analysis, and machine learning techniques.

• Soft Skills:

• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.
• Detail-oriented with a focus on data accuracy.

Preferred Skills:

• Experience working with networking and firewalls for real-time data integration.
• Exposure to Industry 4.0 concepts, including CBMS and digital twins.
• Hands-on experience with scripting and automation of reports.