Data Scientist(Image processing) (NCS/Job/ 2009)

Degree and Qualification:

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

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

Number of Years of Experience as a Data Analyst / Scientist: 3-8 years

Language Skills:

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

Domain Knowledge:

• Strong understanding of supply chain and supplier performance evaluation processes.

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

• Basic knowledge of plant logistics and operational efficiency.

Technical Skills:

• 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):

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

   • 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.

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

   • 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): Experience in publishing, refreshing, and managing reports in Power BI Service, including RLS and data gateways.

2. Machine Learning & AI:

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

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

3. Data Wrangling & Analysis:

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

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

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

4. Communication & Stakeholder Management:

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

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

Behavioral / Personal Skills:

• Willingness to learn and apply new skills.

• High adaptability and readiness to handle unstructured tasks.

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

• Team player with excellent communication and interpersonal skills.