Data Scientist

Role & responsibilities

Experience in Data Science and AI / ML domain

Excellent understanding of machine learning techniques and algorithms, such as GPTs, CNN, RNN, k-NN, Naive Bayes, SVM, Decision Forests, etc.

Experience using business intelligence tools (e.g. Tableau, PowerBI) and data frameworks (e.g. Hadoop)

Experience in Cloud native skills.

Knowledge of SQL and Python; familiarity with Scala, Java or C++ is an asset

Analytical mind and business acumen and Strong math skills (e.g. statistics, algebra)

Experience with common data science toolkits, such as TensorFlow, KERAs, PyTorch, PANDAs, Microsoft CNTK, NumPy etc. Deep expertise in at least one of these is highly desirable.

Experience with NLP, NLG and Large Language Models like BERT, LLaMa, LaMDA, GPT, BLOOM, PaLM, DALL-E, etc.

Great communication and presentation skills. Should have experience in working in a fast-paced team culture.

Experience with AIML and Big Data technologies like AWS SageMaker, Azure Cognitive Services, Google Colab, Jupyter Notebook, Hadoop, PySpark, HIVE, AWS EMR etc.

Experience with NoSQL databases, such as MongoDB, Cassandra, HBase, Vector databases

Good understanding of applied statistics skills, such as distributions, statistical testing, regression, etc.

Should be a data-oriented person with analytical mind and business acumen

Preferred candidate profile