Rocket Software Recruitment Drive | Hiring Assistant Data Scientist | Fresher

• 0 -2 years of relevant industry experience or fresh graduates are welcome to apply.
• Good knowledge of Python and Linux, familiarity with ML frameworks, and a willingness to learn.
• Demonstrated problem-solving abilities and creative thinking.
• Basic experience or understanding in applying Data Science methodologies to extract, process, and transform data from multiple sources.
• Excellent communication and interpersonal skills.
• Must be comfortable working in a team-oriented environment.

R Rocket's Data Modernization Business Unit aids customers in managing, governing, and maximizing the value of their enterprise data assets. Our clientele comprises many Fortune 500 companies, including some of the world's largest banks, insurance companies, and manufacturing organizations. We are currently seeking motivated and innovative individuals to join our applied machine learning team. This is an opportunity to play a crucial role in the continued evolution of our world-class solutions.

The Data Science Assistant will assist and learn from the Principal and Senior Data Scientists. They will help in creating, fine-tuning, and deploying advanced machine learning models. The position requires a foundational understanding of Python programming, computational linguistics, and image processing. This is an exceptional opportunity for growth and learning, presenting the chance to work with a team dedicated to state-of-the-art models and real-world problem-solving.

Essential Duties and Responsibilities

• Assist in developing, fine-tuning, and deploying machine learning models.
• Aid in consulting with key internal and external stakeholders to understand and frame model requirements and potential applications.
• Participate in the development of sound analytic plans based on available data sources, business partner needs, and required timelines.
• Work with software engineers in integrating trained models into end-user applications.
• Help manage deliverables across multiple projects in a deadline-driven environment.
• Present results, insights, and recommendations to both technical and non-technical stakeholders.