Micron Technology is hiring for a fresher entry level Data Scientist role in India

Position:

Data Scientist

Company:

Micron Technology, Inc.

Location:

Sanand, Gujarat, India

Job type:

Full-time

Job mode:

On-site

Job requisition id:

JR58215

Years of experience:

Not explicitly mentioned (open to freshers and experienced candidates); 0-3 years

Company description:

Micron Technology is at the forefront of revolutionizing the way the world stores, accesses, and processes data.
It stands as a global leader in memory and storage innovations, playing a crucial role in the growth of the data economy.
The company is recognized for its commitment to transforming massive data into actionable intelligence that drives technology forward.
Through its brands such as Micron® and Crucial®, the organization delivers an extensive range of cutting-edge DRAM, NAND, and NOR memory solutions.
These offerings support AI-driven platforms, 5G technologies, data centers, mobile applications, and edge computing.
At its core, Micron operates with a vision to enrich life for everyone by enabling faster learning, communication, and advancement.
With strong values rooted in customer satisfaction, operational excellence, and innovation, the company fosters a culture of integrity and diversity.
Employees are encouraged to learn continuously, contribute to meaningful projects, and take part in building technologies that impact global industries.
Sustainability and community development are central to Micron’s operations, ensuring it remains responsible and impactful beyond business metrics.
From employee well-being initiatives to community engagement and environmental responsibility, Micron takes a holistic approach to corporate citizenship.

Profile overview:

This position is ideal for individuals with a passion for data science and a desire to work at the intersection of advanced analytics and high-tech manufacturing.
As a Data Scientist at Micron, you'll be working with extremely large volumes of data from varied sources, enabling process automation and predictive insights.
You’ll participate in transforming raw data into meaningful patterns and solutions that support strategic decisions and production enhancements.
The role involves significant engagement with statistical modeling, machine learning, and the development of intelligent applications.
You’ll need to apply your analytical expertise to uncover insights from structured and unstructured data and use these insights to recommend improvements.
Candidates must be comfortable with data wrangling, exploration, and visualization using modern tools and programming languages.
There's also an opportunity to build web applications and APIs as part of broader projects, integrating AI and data science into real-world interfaces.
Cloud-based analytics, distributed computing, and application development are core parts of the work environment.
Collaboration is key – you’ll work alongside cross-functional teams and contribute to shared goals through analytical solutions.
Ideal candidates are adaptable, self-driven, and capable of learning new technologies in a dynamic setting.

Qualifications:

A Bachelor's or Master’s degree in Computer Science, Electronics, or Electrical Engineering is required.
Candidates should have secured at least a 7.0 CGPA or higher in their academic programs.
Proficiency in Python is essential, along with a strong foundation in statistics and machine learning principles.
Experience with SQL and other database querying tools is necessary for effective data extraction and transformation.
Candidates should be comfortable using techniques like outlier detection, data cleaning, and handling missing values.
Familiarity with front-end technologies like JavaScript and AngularJS 2.0 is an added advantage, especially for web application development.
Knowledge of data visualization tools like Tableau is desirable.
Understanding of object-oriented programming concepts adds value.
Exposure to distributed computing frameworks like pySpark and related libraries is beneficial.
Experience with TensorFlow and other statistical/machine learning libraries is helpful for model development and deployment.
Applicants should be enthusiastic about working with time series, image data, or data affected by shifting patterns and distributions.
Prior exposure to Manufacturing Execution Systems (MES) is considered a plus.

Roles and Responsibilities:

Core Responsibilities:

Interpret and analyze vast amounts of structured and unstructured data from various sources in the manufacturing domain.
Develop machine learning models that optimize manufacturing processes and predict equipment behaviors.
Build applications and tools that integrate advanced analytics into business operations.
Design and implement data pipelines for real-time or batch analytics.
Apply advanced statistical and mathematical techniques to solve business and operational challenges.
Collaborate with engineering, IT, and business stakeholders to identify data science opportunities.
Present findings clearly through visualizations, dashboards, and written communication.

Technical Skills & Tools:

Demonstrated proficiency in Python for data manipulation, analysis, and modeling.
Expertise in SQL for data extraction from relational databases.
Working knowledge of machine learning models including supervised, unsupervised, and semi-supervised approaches.
Exposure to cloud platforms (e.g., AWS, Azure) for scalable analytics solutions.
Familiarity with time series forecasting, anomaly detection, and image processing is advantageous.
Web application development experience is a strong plus.
Ability to build and manage APIs for integrating models and applications.
Knowledge of big data tools such as Spark, Hadoop, and distributed systems is helpful.

Collaboration & Communication:

Work with cross-functional teams to understand project goals and define analytical needs.
Share results and models with technical and non-technical stakeholders.
Document data processes, model assumptions, and decision-making logic thoroughly.
Be proactive in identifying areas for improvement or automation through data science.
Maintain open communication with distributed global teams to ensure alignment and clarity.

Innovation & Learning:

Stay updated with the latest research and tools in the data science and machine learning space.
Experiment with new technologies and methodologies to enhance existing processes.
Take ownership of learning new skills that align with Micron’s long-term digital transformation goals.
Participate in knowledge-sharing sessions, hackathons, or internal R&D initiatives.

Additional info:

Work Environment & Culture:

The Sanand facility is part of Micron’s strategic manufacturing expansion and serves as a hub for innovation in India.
The company supports a fast-paced and intellectually stimulating environment where professionals grow and thrive.
Team members are encouraged to take initiative, innovate, and push boundaries in both technology and process excellence.
Open communication, diversity, and mutual respect are deeply embedded in the company’s culture.
The role provides opportunities to interact with global teams and contribute to large-scale industrial AI applications.

Perks and Benefits:

Competitive compensation packages, aligned with industry benchmarks and performance metrics.
A wide array of health benefits including medical, dental, and vision insurance for employees and families.
Employee stock purchase program allows team members to buy Micron stock at a discounted rate.
Generous paid time off and leave policies to maintain a healthy work-life balance.
World-class learning resources and programs to support career development.
Peer-to-peer recognition programs to celebrate achievements and contributions.
Opportunities to volunteer and give back through the Micron Foundation.
Wellness programs focused on mental, physical, and emotional health.
Transparent hiring practices and zero tolerance for discrimination or recruitment fees.
Strict compliance with all labor laws, including prohibition of child labor and unethical employment practices.
Flexible project assignments and global mobility options may be considered for top-performing individuals.