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    Job · 23468162

    Applied Materials logo

    Sr Data Scientist

    Applied Materials · Bengaluru · onsite · Posted 1d ago

    Undisclosed8–13 yrsfulltimeSourced fromNaukri

    About a minute. You'll make an account on the way through.

    About this role

    Role Overview
    As a Data Scientist, you will develop data-driven insights, predictive models, and optimization solutions that improve semiconductor manufacturing operations. You will work closely with customers, domain experts, and engineering teams to transform large-scale manufacturing and simulation data into actionable recommendations and intelligent decision-support capabilities.
    The role combines statistical analysis, machine learning, optimization, simulation, and experimentation. You will contribute to both customer projects and internal innovation efforts while helping bridge the gap between business challenges and technical solutions.
    Location: Bangalore


    Key Responsibilities

    Data Analysis & Insights
    • Collect, process, and analyze manufacturing, simulation, and operational datasets.
    • Perform exploratory data analysis (EDA) to identify trends, bottlenecks, anomalies, and opportunities for improvement.
    • Develop statistical models and analytical frameworks to support operational decision making.
    • Translate complex analytical findings into clear business recommendations.


    Modeling & Optimization
    • Design, develop, and validate predictive models for forecasting, classification, anomaly detection, and optimization use cases.
    • Apply operations research, statistical learning, and optimization techniques to solve manufacturing challenges.
    • Contribute to hybrid solutions that combine analytics, machine learning, and simulation technologies.
    • Design experiments and perform rigorous analysis to validate model effectiveness and business impact.


    Simulation & Manufacturing Intelligence
    • Work with simulation technologies, including discrete-event simulation (DES), to evaluate manufacturing scenarios and operational strategies.
    • Analyze simulation outputs and combine them with historical operational data.
    • Develop methodologies that improve planning, scheduling, resource utilization, and factory performance.


    Collaboration & Communication
    • Work directly with customers, domain experts, and project teams to understand business requirements.
    • Present technical findings and recommendations to both technical and non-technical audiences.
    • Document datasets, methodologies, experiments, and analytical conclusions.
    • Contribute to customer workshops, solution design sessions, and project reviews.


    Research & Innovation
    • Stay current with developments in data science, statistics, optimization, and applied machine learning.
    • Evaluate emerging methodologies and identify opportunities to improve customer outcomes.
    • Support research initiatives focused on manufacturing intelligence and decision-support technologies.


    Required Skills
    • Strong foundation in statistics, mathematics, and data analysis.
    • Experience developing predictive and analytical models.
    • Strong Python programming skills.
    • Hands-on experience with Pandas, Polars, NumPy, Scikit-learn, and related analytical tooling.
    • Experience with feature engineering, exploratory analysis, and model evaluation.
    • Understanding of optimization techniques, statistical experimentation, and hypothesis testing.
    • Strong problem-solving and analytical thinking skills.
    • Ability to communicate technical concepts to diverse stakeholders.


    Preferred Skills
    • Experience with discrete-event simulation or operations research.
    • Experience with manufacturing, scheduling, supply chain, or industrial systems.
    • Familiarity with machine learning deployment and MLOps concepts.
    • Experience working with high-dimensional or time-series datasets.
    • Knowledge of semiconductor manufacturing or advanced industrial environments.
    Experience - 8+ Years


    About the Team
    You will be joining a highly experienced team of data scientists, AI engineers, software developers, and cloud architects, many with over a decade of experience delivering innovative solutions across multiple industries. Our work spans embedded software, renewable energy optimization, advanced scheduling systems, and AI-driven decision support platforms for multi-billion-dollar semiconductor fabrication facilities.
    At Applied Materials, your work will directly influence customer outcomes and business success. As a focused and highly collaborative team, every member plays a meaningful role in shaping both technical solutions and company direction.
    No two days are the same. You'll face new challenges, learn continuously, and contribute to solving some of the most difficult problems in industrial AI and optimization. Our customers engage us because they need solutions that go beyond conventional approaches, giving our team the opportunity to create truly unique and impactful technology.


    Additional Information
    • Time Type: Full time
    • Employee Type: Assignee / Regular
    • Travel: Yes, 10% of the Time
    • Relocation Eligible: Yes

    Sourced from naukri

    Skills

    classificationBusiness Requirementsdata scientistfeature engineeringEmbedded SoftwareAnalyticsExploratory Data AnalysisAnomaly DetectionEvent DrivenEmbedded SystemsdeploymentcloudFabricationdata analysisData ScienceArtificial IntelligenceForecasting

    About Applied Materials

    Applied Materials logo

    Applied Materials

    Semiconductors

    3.5k+

    employees

    2002

    24 years old

    Santa Clara, California

    United States (USA)

    About

    Applied Materials, Inc. is the global leader in materials engineering solutions for the semiconductor, flat panel display, and solar photovoltaic industries.

    Industries

    SemiconductorsManufacturingEngineering & Construction

    Employee ratings

    573 reviews

    3.7/ 5

    Culture

    3.7

    Career growth

    3.1

    Work-life

    3.6

    Employees rate it well for

    Work Life Balance94Work Culture74Senior Management54Salary53Learning43

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