
Chief Data Architect
1 week ago
We are seeking an accomplished Data Scientist to spearhead advanced Machine Learning (ML), Deep Learning, Natural Language Processing (NLP), and Computer Vision (CV) initiatives.
Design and develop sophisticated data science solutions by harnessing structured and unstructured data.
Utilize predictive modeling, statistics, trend analysis, and other data analysis techniques to uncover valuable insights and address specific research questions.
Collaborate with cross-functional teams to enhance the effectiveness of computational models through data-driven decision-making and stakeholder feedback.
Support the development of machine learning models under the guidance of senior colleagues.
Mentor junior data science team members, as needed.
- Minimum 5 years of experience as a Data Scientist or ML Engineer in AI/ML projects.
- Strong expertise in Machine Learning, Deep Learning, NLP, and Computer Vision techniques.
- Hands-on experience with Generative AI models (LLMs, VLMs, MLLMs), and knowledge of multi-modal neural networks and Transformer architectures.
- Proficiency in Python, R, and key ML/DL libraries (Scikit-learn, Pandas, TensorFlow, PyTorch, etc.).
- Strong understanding of SQL-based and NoSQL databases (MySQL, PostgreSQL, Oracle, MongoDB).
- Experience with statistical tools and platforms like WEKA, KNIME, Power BI, etc.
- Working experience with Big Data technologies – HDFS, Spark, Hive, Sqoop, MapReduce.
- Good understanding of cloud platforms (AWS, Azure, or GCP) – any hands-on experience is beneficial.
- Excellent analytical, problem-solving, and communication skills.
- Domain expertise in Automotive, Manufacturing, E-commerce, Aviation, or Digital Platforms is highly desirable.
- Education: A bachelor's degree in computer science, computer engineering, information technology, or a related field is typically the minimum requirement. A master's degree in data science or a related field is preferred for advanced roles.
- Experience: Data Scientists require at least 5 years of experience in related fields such as database administration, data engineering, programming, and data analytics.
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