Data Scientist(Image processing)

Degree and Qualification:

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  BE/B.Tech, ME/M.Tech in CSE/IT, Statistics, or a related field.



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  Master s degree in data science, AI, or a related field is preferred.

Number of Years of Experience as a Data Analyst / Scientist:

Language Skills:

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  Good communication skills in English, proficiency in German is an added advantage.

Domain Knowledge:

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  Strong understanding of supply chain and supplier performance evaluation processes.



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  Familiarity with procurement, supplier management, inbound processes, and logistics concepts like goods receipt, delivery note, and part numbers.



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  Basic knowledge of plant logistics and operational efficiency.

Technical Skills:

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  Python, PySpark, SQL, Power BI (Advanced Level), Databricks, Azure/AWS, Machine Learning, Data Visualization, TensorFlow, PyTorch, and deploying ML models in production.

Digital Expertise:

1. Power BI Desktop (advanced):

   
   
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     Advanced knowledge of building dashboards, creating data models, and writing DAX expressions.

   
   
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     Ability to develop custom visualizations in Power BI using Python scripts / other suitable methods to create charts and data representations not supported natively by Power BI.

   
   
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     Ability to write Python scripts to process and transform data within Power Query for advanced analytics and visualization scenarios.

   
   
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     Strong design / Power BI UI/UX skills to ensure Power BI dashboards aligns with business objectives and effectively tells a data-driven story.

   
   

   • Power BI Service (advanced):

   
   
   
   



2. Machine Learning & AI:

   
   
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     Experience in building predictive models using machine learning algorithms such as regression, classification, clustering, and anomaly detection.

   
   
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     Familiarity with AI concepts like neural networks, NLP, or reinforcement learning.

   
   
   
   



3. Data Wrangling & Analysis:

   
   
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     Proficiency in Python and popular data libraries like Pandas, NumPy, and Scikit-learn.

   
   
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     Experience in PySpark for distributed data processing and large-scale data transformation.

   
   
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     Strong SQL skills for querying relational databases, optimizing queries, and handling complex datasets.

   
   
   
   



4. Communication & Stakeholder Management:

   
   
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     Ability to effectively communicate technical insights to non-technical stakeholders.

   
   
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     Strong customer-facing communication skills and experience collaborating with cross-functional teams.

   
   
   
   

Behavioral / Personal Skills:

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  Willingness to learn and apply new skills.



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  High adaptability and readiness to handle unstructured tasks.



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  Strong analytical mindset, with a focus on problem-solving and result-oriented thinking.



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  Team player with excellent communication and interpersonal skills.