ML Lead
1 week ago
- Role: Individual will be responsible for overseeing a team of data scientists and driving data-driven decision-making within the organization
- Key Responsibilities:
- This role will involve developing, implementing, and managing advanced analytics and machine learning models to extract insights and create predictive solutions.
- Build solutions using Statistics, Machine Learning, Deep Learning or Generative AI
- Interact with client for understanding requirements and discussing solutions
- Set clear goals, assign tasks, and ensure the team's performance meets or exceeds expectations.
- Identify new data sources and technologies that can improve data analysis and modeling capabilities.
- Ensure data privacy and compliance with relevant regulations
- Job Requirement:
- Bachelors or higher degree in a relevant field like Computer Science, Statistics, Mathematics, Engineering
- 8+ years industry experience in a data science or Machine Learning projects & at least 2 years of experience in Leading a Data Science or ML teams with 3 or more members.
- Strong experience in Machine Learning is a must with an acumen for statistical analysis of structured data
- Experience in Deep Learning, Computer Vision is not critical and is optional
- Generative AI is not critical but good to have skill
- Should have implemented solutions using various ML models such as SVM, Random Forest, XG Boost, prediction modelling, forecasting modelling, anomaly detection
- Strong programming skills in languages such as Python, PySpark and SQL
- Expertise and fluency in ML technologies & frameworks such as Scikit Learn, PANDAS, Numpy, Spark, etc
- Exposure to MLOps and Model Training Pipeline development on cloud will be an advantage
- Experience in frameworks such as TensorFlow, Keras, PyTorch is not critical and is optional
- Experience of requirement understanding & solution designing
- Good to have knowledge in Generative AI techniques prompt engineering, LLMs, Vector DB
- Familiarity with Cloud platforms, particularly Azure, AWS or GCP, and expertise in designing, developing, and deploying cloud-based solutions
- Excellent problem-solving skills and the ability to translate business questions into data science projects.
- Strong leadership, communication, and project management skills.
- Exceptional standards for quality and strong attention to detail.
- Ability to manage multiple projects and on-demand business requests simultaneously.
- Relevant certifications (e.g., Azure Data Scientist Associate, AWS ML Specialty) can be an advantage
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