Data Scientist 2

The group you’ll be a part of

Global Business Intelligence Solutions - AI Hub

The impact you’ll make

Join Lam as a Data Scientist, where you'll design, develop, and program methods to analyze unstructured and diverse big data into actionable insights. You'll develop algorithms and automated processes to evaluate large data sets from disparate sources. Your expertise in generating, interpreting, and communicating actionable insights enables Lam to make informed and data-driven decisions.

What you’ll do

Who we’re looking for

• Master’s degree in Data Science , Computer Science, or a related field.

Preferred qualifications

Eligibility Criteria:

• Master’s degree in Data Science , Computer Science, or a related field.
• Strong programming skills in Python and proficiency with relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Solid understanding of machine learning algorithms, statistical concepts, and data structures.
• Well versed with data preprocessing, feature engineering, and model evaluation.
• Excellent problem-solving skills and the ability to work in a collaborative, fast-paced environment.
• Strong communication skills to convey complex technical concepts to non-technical stakeholders.
• Cut off percentage: 65% Aggregate (No backlog as of now)

Primary Responsibilities:

• 
  Collaborate with cross-functional teams to understand business requirements and identify opportunities for applying machine learning solutions.
• Design, develop, and implement machine learning models to address complex problems, leveraging both structured and unstructured data.
• Perform data preprocessing, feature engineering, and exploratory data analysis to ensure the quality and relevance of datasets.
• Develop, Evaluate and fine-tune models for optimal performance, considering factors such as accuracy, precision, recall, and computational efficiency.
• Stay abreast of the latest advancements in machine learning and actively contribute ideas to enhance our technical capabilities.
• Work closely with software engineers to integrate machine learning models into production systems.

Mandatory Skills:

• Strong hold on Python
• Strong understanding of Machine Learning and Deep Learning concepts
• Strong analytical, logical, problem solving, trouble shooting skills
• Excellent communication skills
• Interested in semiconductor domain and keen to work in wafer-fabrication equipment software stack

Desirable Skills:

• Knowledge of OOPS concepts
• Knowledge of SQL server
• Knowledge of Data transformation and Different data structures

Our commitment

We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results.

Lam Research ("Lam" or the "Company") is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees.

Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories – On-site Flex and Virtual Flex. ‘On-site Flex’ you’ll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. ‘Virtual Flex’ you’ll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.