Data Scientist - Bengaluru, India - Mercedes-Benz Research and Development India Private Limited

Mercedes-Benz Research and Development India Private Limited

Verified Company

Bengaluru, India

2 weeks ago

Posted by:

Deepika Kaur

beBee Recuiter

Description

Aufgaben
Position Overview:
We are seeking a skilled and experienced Data Scientist with expertise in supply chain forecasting to join our team.

As a Data Scientist for Supply Chain Forecasting, you will be responsible for developing and implementing advanced analytical models and algorithms using Azure ML and Databricks.

Additionally, your experience in API development and deployment will be essential for integrating and operationalizing the forecasting models. Your role will contribute to optimizing our supply chain operations, enhancing demand forecasting accuracy, and driving data-driven decision making.

Key Responsibilities:

Data Analysis and Preprocessing:

Collect, clean, and preprocess large and complex datasets from various sources, including historical sales data, inventory records, market trends, and external factors influencing the supply chain.

Forecasting Model Development:

Utilize Azure ML and Databricks to develop and deploy advanced statistical models, time series forecasting algorithms, and machine learning models to predict future demand patterns, sales volumes, and inventory levels.

API Development and Deployment:
Design, develop, and deploy APIs to facilitate the integration and consumption of forecasting models in production systems. Ensure scalability, reliability, and real-time performance of the deployed APIs.

Data Visualization:
Create insightful visualizations, charts, graphs, and dashboards to communicate complex forecasting results and insights to stakeholders. Enable better understanding and facilitate data-driven decision making.

Optimization:
Collaborate with cross-functional teams, including operations, logistics, and procurement, to identify opportunities for supply chain optimization. Develop models to optimize inventory levels, transportation routes, and production schedules.

Performance Evaluation:
Monitor and evaluate the performance of forecasting models and algorithms, identifying areas for improvement. Implement enhancements to increase accuracy, robustness, and efficiency.

Collaborative Projects:

Work closely with data engineers, software developers, and other data scientists to integrate forecasting models into production systems using Azure ML and Databricks.

Ensure seamless integration and operationalization of the models.

API Documentation and Maintenance:
Document APIs, including endpoints, data structures, and usage instructions. Continuously maintain and update the APIs as per evolving business needs and requirements.

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Qualifikationen
Qualifications and Skills:

Bachelor's or master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Operations Research, or a related discipline.

Strong experience in data analysis, statistical modeling, and machine learning techniques.

Proficiency in Azure ML and Databricks for model development, deployment, and management.

Experience in API development and deployment, including designing and consuming RESTful APIs.

Strong programming skills in languages such as Python, R, or SQL.

Experience with data manipulation, cleaning, and feature engineering.

Familiarity with time series forecasting methods, such as ARIMA, exponential smoothing, or Prophet.

Proficiency in data visualization tools such as Tableau, Power BI, or matplotlib.

Strong problem-solving abilities and the capability to translate business requirements into analytical solutions.

Excellent communication and presentation skills to effectively convey complex concepts to both technical and non-technical stakeholders.

Join our team as a Data Scientist for Supply Chain Forecasting and contribute to optimizing our supply chain operations using Azure ML and Databricks.

Your expertise in API development and deployment will be crucial in integrating and operationalizing the forecasting models, enabling data-driven decision making and maximizing our supply chain performance.