Scientist 5, Data Science, Generative AI, MLOps and Data engineering , 12+ years

Lead end-to-end development of machine learning and AI models for predictive analytics, optimization, and automation. Architect and implement scalable data pipelines for ingestion, transformation, and storage of large datasets using Big Data technologies. Develop advanced algorithms leveraging techniques from machine learning, deep learning, and statistical modeling. Collaborate with cross-functional teams to integrate models into production systems and ensure alignment with business objectives. Drive technical leadership and innovation by exploring emerging technologies and methodologies to enhance data-driven decision-making. Document and present findings to technical and non-technical stakeholders, ensuring clarity and actionable insights. Mentor and guide junior data scientists, fostering a culture of continuous learning and technical excellence.

Must Have

• Lead end-to-end development of machine learning and AI models
• Architect and implement scalable data pipelines using Big Data technologies
• Develop advanced algorithms leveraging ML, deep learning, and statistical modeling
• Collaborate with cross-functional teams to integrate models into production systems
• Drive technical leadership and innovation
• Master’s in Computer Science, Data Science, Statistics, or related field
• 8+ years of industry experience in data science, machine learning, or AI
• Proficiency in Python, R, TensorFlow, PyTorch, or Scikit-learn
• Strong knowledge of SQL/NoSQL databases and Big Data technologies (Hadoop, Spark)
• Expertise in cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes)
• Solid understanding of data structures, algorithms, and software engineering principles
• Experience with Natural Language Processing (NLP), Computer Vision, Generative AI
• Proven track record of deploying ML models at scale in production environments

Job Description

• Lead end-to-end development of machine learning and AI models for predictive analytics, optimization, and automation.
• Architect and implement scalable data pipelines for ingestion, transformation, and storage of large datasets using Big Data technologies.
• Develop advanced algorithms leveraging techniques from machine learning, deep learning, and statistical modeling.
• Collaborate with cross-functional teams to integrate models into production systems and ensure alignment with business objectives.
• Drive technical leadership and innovation by exploring emerging technologies and methodologies to enhance data-driven decision-making.
• Document and present findings to technical and non-technical stakeholders, ensuring clarity and actionable insights.
• Mentor and guide junior data scientists, fostering a culture of continuous learning and technical excellence.

Qualifications

• Master’s in Computer Science, Data Science, Statistics, or related field.
• 8+ years of industry experience in data science, machine learning, or AI.
• Proficiency in Python, R, and frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Strong knowledge of SQL/NoSQL databases and Big Data technologies (Hadoop, Spark).
• Expertise in cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Solid understanding of data structures, algorithms, and software engineering principles.
• Experience with Natural Language Processing (NLP), Computer Vision, Generative AI (MCPs).
• Proven track record of deploying ML models at scale in production environments.
• Strong communication and technical leadership skills.
• Advanced problem-solving and analytical thinking.

Additional Information

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