2 дня назад
Data Scientist (AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Scientist (AI) (Generative AI/ML): Designing and deploying AI and machine learning models for scientific and business problems with an accent on Generative AI, large language models, RAG, and experimentation. Focus on preparing large-scale datasets, evaluating model accuracy, robustness, and fairness, and translating analytical findings into actionable product and business insights.
Location: Hyderabad, India
Company
is an independent scientific organization that develops quality standards for medicines, dietary supplements, and food ingredients.
What you will do
- Design, develop, and deploy AI and machine learning models for business and scientific problems, with a focus on Generative AI.
- Collaborate with data engineers to access, clean, and prepare large-scale datasets.
- Perform exploratory data analysis, hypothesis testing, and feature engineering.
- Evaluate and improve model accuracy, robustness, interpretability, and fairness.
- Translate analytical findings into actionable insights for product, engineering, business, and other stakeholders.
Requirements
- Bachelor’s degree in engineering, analytics, data science, computer science, statistics, or a related field, or equivalent experience.
- 1–3 years of experience in data science with expertise in artificial intelligence, machine learning, deep learning, and reinforcement learning.
- Hands-on experience with Generative AI, large language models, RAG, prompt engineering, and vector databases such as FAISS or Pinecone.
- Strong programming skills in Python and PySpark, plus experience with scikit-learn, TensorFlow, PyTorch, or Hugging Face Transformers.
- Strong SQL, data visualization, model evaluation, interpretability, and production deployment skills.
- Familiarity with Azure, AWS, or GCP and ability to collaborate with business, product, program, architecture, and engineering stakeholders.
Nice to have
- Experience with scientific chemistry nomenclature, life sciences, chemistry, hard sciences, pharmaceutical datasets, or pharmaceutical nomenclature.
- Experience with MLOps tools and practices such as MLflow, Kubeflow, or Azure ML.
- Strong verbal, written, and interpersonal communication skills.
Culture & Benefits
- Work within a mission-driven scientific organization focused on safe, quality medicines and supplements.
- Collaborate with more than 1,100 professionals across global locations.
- Company-paid time off, comprehensive healthcare options, and retirement savings benefits.
- Inclusive and equitable workplace practices centered on quality and patient safety.
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