Jr. Data Analyst

3 days ago

Chennai, Tamil Nadu, India Proterial Full time ₹ 9,00,000 - ₹ 12,00,000 per year

Location:

Chennai, Tamil Nadu, India

Job ID:

R0103053

Date Posted:

Company Name:

HITACHI ENERGY TECHNOLOGY SERVICES PRIVATE LIMITED

Profession (Job Category):

Engineering & Science

Job Schedule:

Full time

Remote:

No

Job Description:

  • Responsible for supporting the Sales and Strategic Marketing functions of the global Business Unit (BU) High Voltage in understanding market, competitor trends and Price performance by developing and implementing state-of-the-art data Analytics model as well as process and tool support.
  • Understand the product & market segmentation of portfolio and build know-how of data eco systems in various process involved in Business.
  • Prepare reports with clear information understanding the raw information and interpret the date in optimized KPIs (target achievement, Price performance, Order trend, pipeline development, etc), profitability.
  • Collaborate with Global, HUB & Pricing specialist to develop and implement competitive strategies, etc.
  • Be in charge of the development and updation of models using Python as well as related user training in order to increase the analytical capabilities of our sales management around the globe.
  • Responsible to continuously improve process performance and data quality
  • Document and follow the guidelines for the efficient business
  • Assess data from different sources to gain insights into pricing strategies and market trends.
  • Analyze historical sales data to identify trends, patterns, and insights that can drive business decisions.
  • Develop and implement predictive models to forecast future sales and demand for power system products.
  • Collaborate with CFT to understand business requirements and translate them into analytical solutions.
  • Perform data cleaning, preprocessing, and validation to ensure data quality and accuracy.
  • Utilize machine learning algorithms and statistical techniques to build robust models.
  • Continuously monitor and improve model performance based on feedback and new data.
  • Stay updated with the latest industry trends and advancements in data science and machine learning.
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