Top 10 Data Science jobs to apply for this week

The Top 10 data science jobs to apply for this week this list is constantly updated

As the world shifts toward a more data-driven and analytical approach to making judgments based on facts rather than instincts, practically every firm, from small to large, hires experienced data scientists. Here are the top 10 data science jobs to apply for this week.

1. Junior Data Scientist at Bento Labs (Hyderabad)

Responsibilities: identifying value in the data we have; preparing structured and unstructured data; exploring multiple channels to obtain new data to assist the analytics and models; and analyzing vast volumes of data to detect trends and patterns. Create predictive models and machine-learning algorithms; Present information using data visualization techniques.

2. Data Scientist at Microsoft (WFH)

Enterprise Analytics and Tools (EAT / RISE / PACE) is a team inside the EC organization that develops tools and services to support this expansion. You will design, implement, integrate, and improve these systems. Our team is made up of highly driven and inventive engineers. 

3. Data Scientist at Yash Technologies (Hyderabad)

You will collaborate with a specialized team of professionals comprising researchers, developers, DevOps engineers, and architects to design the finest machine learning pipelines for a wide range of use cases, including commerce, agriculture, insurance, financial markets, and procurement.

4. Jr. Data Scientist at Finbots.AI (Hyderabad) 

Responsibilities: Obtaining relevant data, developing hypotheses, and generating conclusions from the data using suitable statistical procedures. Creating products, prototypes, and MVPs to verify ideas through the practical use of data science. Assisting with Proof of Concept (POC) projects with customer businesses.

5. Senior analyst data science at AOS(India)

Roles and responsibilities include the following: Evaluate and solve more difficult issues. Engage with peers daily inside Navit. Interact with customers and Navit management. She received limited teaching on everyday duties and substantial instruction on new assignments. Seek and deliver relevant and actionable feedback to all contacts consistently. 

6. Senior Data Scientist at Quantium (Hyderabad)

You want to work where you are appreciated and regarded as an individual rather than a number. Quantium is committed to creating a flexible, supportive workplace for its team members, clients, and partners. 

7. Lead Data Scientist at Franklin Templeton (Hyderabad) 

Responsibilities: The position of Lead Data Scientist will be critical in our Distribution Intelligence team. You will lead the use of data to plan, implement, and measure our distribution strategy in collaboration with Franklin Templeton Distribution. Your responsibilities will include a broad spectrum of distribution-related data, including market, product, client, and engagement information. 

8. Data Scientist Azure at Wipro (Hyderabad) 

Responsibilities:  Work with data scientists to develop and implement end-to-end production quality machine learning models and systems. Using continuous integration and deployment, transform and develop sophisticated machine learning models into scalable, reliable, secure, and maintainable machine learning-enabled software solutions. Develop and maintain machine learning services API endpoints for AI model integration and adoption in collaboration with other technical teams. 

9. Lead Data Scientist at Sanofi (Hyderabad)

Responsibilities: You will create globally scalable AI solutions for the benefit of our global patients and customers that are strategically prioritized by the Sanofi commercial area across Global Business Units. Omnichannel Engagement, Anticipating the following best action, Marketing Mix Model, and Smart AI Alerts are some examples of AI initiatives. You will, in particular.

10. Data Science Manager at Innominds Software (Hyderabad) 

Responsibilities: Lead customer engagement in data analytics to transform a client's business challenge and transform it into a data science problem. Data Sources. Acquisition. Alternative Data/ Augmented Data. Transformations. Data Pipelines. Provide research direction and find the best solution to the data science problem through algorithm fit or new algorithm development.