Senior AI/ML Engineer - R01570350

India·BangaloreEmployeesenior

Machine Learning EngineerData

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Quick Summary

Key Responsibilities

Translate complex business challenges into structured data science problems, ensuring alignment with organizational objectives and measurable outcomes Develop, monitor,

Requirements Summary

Advanced proficiency in Python or R for data wrangling, preprocessing, and statistical analysis Expertise in statistical modeling and validation of performance metrics Experience

Technical Tools

Machine Learning EngineerData

Senior Data Scientist

Experience Range: 5 - 8 years of experience, including at least 5 years of hands-on work in data science, analytics, or related fields, with recent exposure to agentic AI solutions Key Responsibilities:

Translate complex business challenges into structured data science problems, ensuring alignment with organizational objectives and measurable outcomes

Develop, monitor, and validate OKRs using advanced statistical techniques to deliver actionable insights and track progress

Execute advanced data wrangling, cleansing, and transformation on large, complex datasets to enable robust modeling and analysis

Deliver impactful data-driven insights through clear data storytelling, utilizing visualization tools to communicate findings effectively to stakeholders

Apply design thinking methodologies to create innovative analytical solutions and continuously optimize data science workflows and processes

Lead technical decision-making for modeling iterations, optimizing model performance, and balancing computational efficiency with business requirements

Collaborate with cross-functional teams, including engineering and product, to implement scalable data science solutions that drive business value

Promote data literacy and foster a culture of data-driven decision-making by sharing best practices and industry trends across the organization

Required Skills:

Advanced proficiency in Python or R for data wrangling, preprocessing, and statistical analysis

Expertise in statistical modeling and validation of performance metrics

Experience with data visualization tools such as Tableau, Power BI, or Matplotlib

Hands-on experience with machine learning algorithms and evaluation metrics

Strong background in feature engineering and data mining

Familiarity with big data technologies such as Spark or Hadoop

Experience with cloud-based data platforms including AWS, Azure, or Google Cloud

Knowledge of MLOps practices and deployment pipelines

Preferred Skills:

Experience with deep learning frameworks such as TensorFlow or PyTorch

Exposure to agentic AI and rapid domain adaptation

Experience with automation tools and scripting for data workflows

Desired Qualifications:

Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline

Certification in Data Science or Machine Learning from a recognized institution, such as Microsoft Certified: Azure Data Scientist Associate or IBM Data Science Professional Certificate

Relevant coursework or certification in statistical analysis or business analytics