Publicis Resources is hiring for a fresher entry level Data Scientist role in India

Position:

• Data Scientist

Company:

• Publicis Re:Sources

Location:

• Gurugram, Haryana, India

Job Type:

• Full-time

Job Mode:

• On-site

Job Requisition ID:

• Not Specified

Years of Experience:

• 0 to 2 years of relevant experience

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Company Description

• Publicis Re:Sources serves as the backbone for Publicis Groupe, the world’s leading agency group.
• Established in 1998 with a modest team, it has since grown into a global organization of over 5,000 employees operating in more than 66 countries.
• The organization specializes in delivering full-service, end-to-end shared services, empowering the agencies under Publicis Groupe to focus on their strengths: innovation and client transformation.
• Publicis Re:Sources provides a diverse range of business services, including technology solutions, finance, accounting, legal, benefits, procurement, tax, real estate, treasury, and risk management.
• Continuously evolving to adapt to the dynamic communications industry, Publicis Re:Sources embraces a culture of innovation that resonates globally.
• For further details about the company and its global impact, visit: http://www.publicisresources.com/.

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Profile Overview

• The role of Junior Data Scientist is pivotal within the organization, requiring a combination of technical proficiency, analytical expertise, and problem-solving skills.
• The selected candidate will be responsible for designing, implementing, and optimizing generative models using advanced machine learning and deep learning methodologies.
• Applications of the role span across diverse domains such as natural language processing (NLP), computer vision, and audio processing, providing a unique opportunity to engage with cutting-edge technologies.
• The role also emphasizes the ability to analyze and interpret vast datasets and effectively communicate insights to diverse stakeholders, both technical and non-technical.
• Collaborating with cross-functional teams, the Junior Data Scientist will contribute to identifying novel opportunities and applications for generative modeling within the organization.
• This role offers an exciting platform for those who are passionate about exploring foundation models and generative AI to make a tangible impact in real-world scenarios.

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Responsibilities

Core Responsibilities:

• Develop and optimize generative models leveraging advanced machine learning and deep learning techniques.
• Apply these models across a variety of fields, including but not limited to natural language processing, computer vision, and audio processing.
• Conduct thorough analysis and interpretation of extensive datasets using statistical and computational methodologies.
• Effectively communicate analytical findings and insights to both technical and non-technical stakeholders, ensuring clarity and actionable outcomes.
• Collaborate with interdisciplinary teams to uncover new use cases and opportunities for the implementation of generative models.

Additional Responsibilities:

• Stay updated on the latest advancements in the foundation models literature and incorporate innovative techniques into project work.
• Design scalable, efficient solutions to address complex data challenges within the organization.
• Mentor junior team members or peers, providing guidance on the application of machine learning and deep learning models.

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Qualifications

Required Qualifications:

• Bachelor’s degree in Computer Science, Data Science, or a related field.
• A strong foundation in machine learning and deep learning principles.
• Familiarity with foundational concepts in the literature of generative and foundation models.
• Hands-on experience in developing, fine-tuning, and optimizing generative models or foundation models.
• Proficiency in programming languages such as Python or R for data analysis and model development.
• Practical knowledge of deep learning frameworks, including TensorFlow and PyTorch.
• Demonstrated ability in problem-solving and analytical thinking to approach complex technical challenges.
• Excellent communication skills to convey technical information effectively to diverse audiences.

Preferred Qualifications:

• Experience in generative models specific to NLP, computer vision, or audio processing, such as LLMs, GANs, VAEs, or diffusion models.
• Familiarity with deploying AI models at scale using frameworks like FastAPI for API deployment, CI/CD pipelines for integration and delivery, and Docker/Kubernetes for containerization and scaling.
• Hands-on experience with cloud platforms such as AWS or Azure, leveraging them for computing and data processing tasks.

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Additional Info

Key Highlights of the Role:

• This position offers a unique chance to engage in groundbreaking projects leveraging generative AI and deep learning techniques.
• It provides exposure to various applications, including NLP, image recognition, and audio analysis, allowing candidates to broaden their expertise across multiple domains.
• Publicis Re:Sources fosters a collaborative and innovative work culture, encouraging professionals to push the boundaries of technology and analytics.
• The role is designed for professionals who are at the beginning of their careers but have a strong technical aptitude and enthusiasm for cutting-edge technologies.

Career Development Opportunities:

• Access to training programs and resources for continuous learning in machine learning, deep learning, and AI technologies.
• Opportunities to collaborate with global teams, gaining insights into diverse markets and industries.
• A chance to contribute to impactful projects that align with the strategic priorities of Publicis Groupe.

Why Join Publicis Re:Sources:

• Be part of a globally recognized organization that values innovation and transformation.
• Work in a dynamic environment that encourages creativity and professional growth.
• Gain hands-on experience with state-of-the-art technologies in data science and AI.
• Enjoy the support of a collaborative team that values diversity and cross-functional collaboration.

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