Data Analyst

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City Of New York rating

7.1

Company rating: 7.1 out of 10

Based on 77 frontline employees who took The Breakroom Quiz

469th of 637 rated public administrative organizations


Job description

Job Description

Job Summary:

We are seeking a results-driven Data Analyst to join our Plant Controlling team and spearhead our analytics and automation initiatives. This is not a traditional reporting role; you will be the catalyst for transforming our data landscape. You will architect and build robust ETL pipelines, develop sophisticated analytical models, and create interactive visualizations that provide unprecedented insight into our manufacturing operations.

This role is a critical business partner to plant leadership, focused on leveraging data to drive strategic decisions in production efficiency, cost management, and inventory optimization. If you are passionate about building scalable data solutions, automating complex processes, and using data science to solve real-world business problems, this is the perfect opportunity to make a tangible impact in a world-class manufacturing environment.

Key Responsibilities:

  • Data Engineering & Automation: * Design, build, and maintain automated ETL pipelines (using tools like Alteryx, Power Query, Python) to extract and consolidate large datasets from SAP (CO, FI, MM) and other plant systems into standardized models for analysis. * Develop and deploy automation scripts (Python, VBA) to streamline financial calculations, month-end closing activities, and reporting workflows, significantly reducing manual effort and improving accuracy. * Architect and implement robust data reporting frameworks, ensuring data integrity and creating a "single source of truth" for key plant metrics.
  • Advanced Analytics & Visualization: * Develop and deploy interactive dashboards in Power BI and/or Tableau to visualize KPIs for executive stakeholders, including production efficiency, cost variances, inventory health, and cash flow trends. * Perform comprehensive variance, trend, and ratio analysis to support FP&A reviews, providing clear commentary on deviations from budget and forecast. * Write and optimize complex SQL queries to support deep-dive analytics into inventory, expenses, and operational performance.
  • Inventory & Cost Controlling: * Conduct in-depth analysis of inventory levels, turnover, and aging to identify slow-moving and obsolete (SLOB) risks and opportunities for optimization. * Support and enhance the physical inventory and cycle counting programs by automating data preparation, discrepancy analysis, and results reporting. * Analyze manufacturing cost variances (material, labor, overhead) to identify root causes and partner with operations to develop corrective action plans.
  • Predictive Modeling & Process Improvement: * (Opportunity for Growth) Implement foundational time-series or regression models (using Python/R) to forecast key metrics like production volume, scrap rates, or inventory needs. * Act as a subject matter expert on data tools and methodologies, training junior team members and promoting a data-driven culture within the plant. * Continuously identify and implement process improvements by leveraging technology to enhance the capabilities and efficiency of the controlling function.

Qualifications:
Qualifications

  • Bachelor’s degree in Data Science, Analytics, Information Systems, Business, Finance, or a related quantitative field. Master's degree is a strong plus.
  • 1-3 years of experience in a data-intensive role such as Data Analyst, Business Analyst, or Financial Analyst with a heavy focus on data manipulation and automation.
  • Proven hands-on experience with an ERP system, with a strong preference for SAP (FI/CO modules).
  • Advanced proficiency in Microsoft Excel, particularly Power Query for ETL and data modeling.
  • Demonstrated experience building automated workflows and ETL pipelines using tools like Alteryx, Python (Pandas), or similar.
  • Expertise in data visualization and creating executive-level dashboards using Power BI or Tableau.

Additional Information

Desired Qualifications:

  • Strong proficiency in writing and optimizing SQL for data extraction and analysis from relational databases.
  • Proficiency in a scripting language like Python or R for data analysis and statistical modeling (e.g., Scikit-learn, Statsmodels).
  • Experience in a manufacturing, supply chain, or financial controlling environment.
  • Solid understanding of cost accounting and inventory management principles.
  • Exceptional problem-solving skills with the ability to translate complex business questions into a clear analytical framework and actionable insights.
  • Excellent communication skills, with the proven ability to present complex data and technical concepts to senior leadership and non-technical stakeholders

** Equal Opportunity Employer, including disability / veterans**

*Bosch adheres to Federal, State, and Local laws regarding drug-testing. Employment is contingent upon the successful completion of a drug screen and background check. Candidates who have been offered the position must pass both screenings before their start date.


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Frequently asked questions

Q: What skills or qualities help someone succeed as a Data Analyst?

A: To succeed as a Data Analyst, key technical skills include proficiency in programming languages such as Python or R, expertise in data visualization tools like Tableau or Power BI, and knowledge of statistical analysis and machine learning concepts. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial for presenting insights to stakeholders and working with cross-functional teams. By combining these technical and soft skills, Data Analysts can drive business decisions, identify areas for improvement, and contribute to the growth and success of their organization.

Q: What is the career path for a Data Analyst?

A: A Data Analyst's typical career progression involves starting as an Entry-Level Data Analyst, where they collect, analyze, and interpret data to inform business decisions. As they gain experience, they can move into Mid-Level roles such as Senior Data Analyst or Business Analyst, where they take on more complex projects and lead smaller teams. Ultimately, they can advance to Senior Leadership positions like Data Scientist, Data Manager, or even Director of Analytics, where they oversee large-scale data initiatives and drive strategic business growth.\n\nKey opportunities for skill development and professional growth in this role include learning programming languages like Python or R, mastering data visualization tools like Tableau or Power BI, and staying up-to-date with emerging trends in machine learning and artificial intelligence. Additionally, Data Analysts can develop soft skills like communication, project management, and leadership to excel in their roles.\n\nLong-term career prospects for Data Analysts are diverse, with potential directions including transitioning into related fields like Business Intelligence, Data Engineering, or even becoming a Product Manager, or pursuing advanced degrees in Data Science or related fields to further specialize in areas like machine learning or data engineering.