AI Strategist

2 days ago

Agra, Uttar Pradesh, India beBeeDataScience Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Job Title: Data Scientist

Data Scientists design and deploy AI/ML strategies that align with business goals, utilizing machine learning algorithms to drive data-driven decision making.

  • Key Responsibilities:
  • Create predictive models to forecast business outcomes using historical data and statistical techniques.
  • Develop cutting-edge machine learning and deep learning models, including neural networks and natural language processing algorithms.
  • Evaluate emerging AI/ML technologies and implement them where beneficial.
  • Design and implement Generative AI solutions for conversational AI experiences.
  • Fine-tune large language models (LLMs) for various business applications, including prompt engineering and model interpretability.
  • Work on text generation, semantic search, intent recognition, and AI-driven recommendation systems.
  • Lead the end-to-end model lifecycle, from data collection and preprocessing to model deployment and monitoring.
  • Implement MLOps best practices to streamline model retraining, CI/CD for ML pipelines, and productionization.
  • Optimize models using hyperparameter tuning techniques such as grid search, Bayesian optimization, and neural architecture search.
  • Guide junior team members on best practices in data science, deep learning, and software engineering.

Required Skills & Qualifications:

  • Education: Bachelor's or Master's degree in Computer Science, Data Science, AI, Statistics, or a related field.
  • Experience: 5+ years of hands-on experience in machine learning, deep learning, NLP, and AI-driven applications.
  • Machine Learning & AI: Proficiency in Classical ML (Regression, Decision Trees, Random Forests, SVMs, Gradient Boosting, etc.) and Deep Learning (CNNs, LSTMs, GANs, Transformers, etc.).
  • Programming & Tools: Proficiency in Python, PyTorch, TensorFlow, NumPy, Pandas, Scikit-learn, and MLOps tools (MLflow, Kubernetes, Docker, AWS SageMaker, Azure ML, etc.).
  • Big Data & Cloud: Experience working with large-scale datasets, cloud-based AI solutions (AWS, Azure, GCP), and distributed computing frameworks (Spark, Dask, Hadoop).

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