ML Data Associate Job at Amazon।30+Vacancies।Apply

Job Role : ML Data Associate

Salary : Rs 3.5-4.5 Lacs P.A

Location : Bengaluru

Company : Amazon

Qualifications : Any Graduate

Experience : 1 – 3 Years

ABOUT AMAZON

Amazon, based by means of Jeff Bezos in 1994, is a international e-commerce and era massive founded in Seattle, Washington. Initially starting as an online bookstore, Amazon has diversified into diverse sectors, including cloud computing, virtual streaming, and artificial intelligence. Its cloud computing department, Amazon Web Services (AWS), is a pacesetter inside the enterprise, providing scalable and dependable cloud solutions for groups international. The business enterprise is likewise recognised for its innovations in logistics and fulfillment, with a substantial community of warehouses and advanced transport systems that ensure speedy and green provider.

Amazon’s commitment to client pride and technological advancement has cemented its function as one of the international’s biggest and maximum influential corporations. Beyond commerce, Amazon is involved in amusement via Amazon Prime Video and has ventured into hardware with merchandise just like the Echo smart speakers. The employer’s broad portfolio reflects its undertaking to be Earth’s most patron-centric enterprise.

Job Description: ML Data Associate

We are in search of an ML Data Associate to assist our information-driven initiatives. The function involves gathering, cleaning, and organizing huge datasets for device gaining knowledge of programs. You’ll assist in growing and preserving records pipelines, making sure information excellent, and taking part with information scientists to optimize version overall performance. Strong analytical capabilities, talent in information processing gear, and experience with SQL and Python are required. The perfect candidate can have a keen eye for element, exquisite trouble-solving abilities, and a ardour for working with facts in a quick-paced surroundings.

Key Responsibilities:

• Data Collection and Management: Gather, smooth, and preprocess huge volumes of information from various resources to make sure accuracy and relevance for gadget learning tasks. Develop and maintain facts pipelines to automate data ingestion and transformation approaches.
• Data Quality Assurance: Perform information validation and first-class tests to become aware of and rectify mistakes or inconsistencies. Implement statistics validation policies and tracking structures to ensure ongoing statistics integrity.
• Data Analysis: Conduct exploratory records analysis (EDA) to recognize facts distributions, become aware of patterns, and extract significant insights. Use statistical methods and visualization equipment to aid statistics-pushed decision-making.(ML Data Associate) 
• Collaboration: Work carefully with statistics scientists, gadget getting to know engineers, and different stakeholders to understand statistics requirements and guide model development. Provide technical guide and guidelines based on information findings.
• Documentation and Reporting: Create complete documentation for statistics processes, together with information assets, modifications, and nice tests. Prepare and present ordinary reviews on data-related activities and findings to control and mission teams.
• Tool and Technology Utilization: Utilize records processing and evaluation gear along with SQL, Python, and facts visualization structures to control and examine records. Stay updated on emerging technologies and pleasant practices in information control and gadget mastering.
• Problem Solving: Troubleshoot records-associated problems and put into effect effective solutions. Continuously improve records methods to decorate performance and accuracy.

Key Skills:

1. Technical Proficiency: Strong understanding of SQL for database querying and Python for records manipulation and evaluation. Familiarity with statistics processing libraries which includes Pandas, NumPy, and Research is critical.
2. Data Management: Experience in dealing with massive datasets and constructing information pipelines. Understanding of ETL (Extract, Transform, Load) strategies and data warehousing standards.
3. Analytical Skills: Ability to perform statistical evaluation, identify tendencies, and derive actionable insights from records. Proficiency in records visualization equipment like Matplotlib, Seaborn, or Tableau.
4. Attention to Detail: High level of accuracy in information coping with and excellent guarantee to ensure reliable and precise effects.(ML Data Associate) 
5. Communication: Strong written and verbal conversation talents to file processes, document findings, and collaborate efficaciously with team members and stakeholders.
6. Problem-Solving: Ability to address and resolve facts-related issues right away, with a proactive approach to identifying and mitigating potential challenges.
7. Adaptability: Flexibility to paintings in a dynamic surroundings, adapt to new equipment and technologies, and live present day with industry tendencies and best practices in information control and machine learning.

Apply Now

Other Job’s

Manager Inside Sales

Service Now Developer

Business Planning Analyst

Senior Cybersecurity Analyst