Senior AI/ML Engineer - R01570350
- Posted
- Employment
- full time
- Work mode
- hybrid
- Experience
- Senior
Senior Data Scientist
Job requirements 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