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

Mercedes-Benz Research and Development India Private Limited

Verified Company

Bengaluru, India

1 week ago

Posted by:

Deepika Kaur

beBee Recuiter

Description

Aufgaben:

you will be part of our dynamic and growing data science team, contributing to the development and implementation of data-driven solutions to support business objectives.

Your primary focus will be on extracting insights from data, building predictive models, and assisting in the creation of data products and analytics tools.

You will work closely with senior data scientists, data engineers, and other cross-functional teams to deliver impactful data solutions.

Key Responsibilities:

Data Analysis and Preprocessing:

Collect, clean, and preprocess data from various sources to ensure its suitability for analysis.
Perform exploratory data analysis (EDA) to uncover patterns, trends, and anomalies.
Collaborate with data engineers to design and maintain data pipelines.

Model Development:
Predictive Analytics:

Use predictive modeling techniques to forecast trends and make data-driven predictions.
Collaborate with stakeholders to understand business requirements and develop relevant analytics solutions.

Data Visualization and Reporting:

Create clear and visually compelling data visualizations to communicate insights effectively.
Generate periodic reports and dashboards to track key performance indicators (KPIs) and monitor model performance.

Machine Learning and AI Implementation:

Support the integration of machine learning and AI models into production systems.
Collaborate with software developers to ensure seamless deployment and functionality.

Continuous Learning:

Stay up-to-date with the latest developments in data science, machine learning, and AI.Participate in workshops, conferences, and training to enhance skills and knowledge.

Qualifikationen:

Required Skills and Qualifications:

Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field.

Strong programming skills in languages such as Python, R, or similar for data manipulation and analysis.
Experience with data visualization tools like Matplotlib, Seaborn, Tableau, or others.

Knowledge of statistical analysis and machine learning techniques (e.g., regression, classification, clustering).Familiarity with popular machine learning frameworks and libraries like Scikit-learn, TensorFlow, or PyTorch.

Proficiency in SQL for data retrieval and manipulation.
Basic understanding of data engineering concepts, including data pipelines and ETL processes.
Excellent problem-solving and analytical skills with a keen attention to detail.