TECHNICAL LEAD - Machine Learning

Happiest Minds Technologies; Maharashtra; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Happiest Minds Technologies is seeking a data scientist to design, develop, and implement machine learning models addressing complex business problems. You will analyze large datasets to extract insights and drive data-informed decisions, while collaborating with cross-functional teams to apply AI/ML across projects.

The role focuses on experiments, model validation, and staying current with AI advances to improve processes.

Qualifications

• Proven experience in machine learning, including supervised and unsupervised learning techniques.
• Strong programming skills in Python, R, or similar languages.
• Expertise in data manipulation and analysis using libraries such as Pandas, NumPy, and Scikit-learn.
• Experience with deep learning frameworks such as TensorFlow or PyTorch.
• Solid understanding of statistical analysis and data visualization techniques.
• Ability to work with large datasets and distributed computing environments.

Responsibilities

• Design, develop, and implement machine learning models and algorithms to solve complex business problems.
• Analyze large datasets to extract meaningful insights and drive data-informed decision-making.
• Collaborate with cross-functional teams to identify opportunities for leveraging AI and machine learning in various projects.
• Conduct experiments and validate models to ensure accuracy and reliability.
• Stay updated with the latest advancements in AI and machine learning technologies and apply them to improve existing processes.
• Mentor and guide junior data scientists and analysts in best practices and methodologies.
• Communicate findings and recommendations to stakeholders through clear and concise reports and presentations.

Skills

ML expertise

Programming (Python/R)

Data manipulation (Pandas/NumPy/Scikit

Tools

Pandas

NumPy

Scikit-learn

TensorFlow

PyTorch

Job description

• Design, develop, and implement machine learning models and algorithms to solve complex business problems.
• Analyze large datasets to extract meaningful insights and drive data-informed decision-making.
• Collaborate with cross-functional teams to identify opportunities for leveraging AI and machine learning in various projects.
• Conduct experiments and validate models to ensure accuracy and reliability.
• Stay updated with the latest advancements in AI and machine learning technologies and apply them to improve existing processes.
• Mentor and guide junior data scientists and analysts in best practices and methodologies.
• Communicate findings and recommendations to stakeholders through clear and concise reports and presentations.

Responsibilities

• Design, develop, and implement machine learning models and algorithms to solve complex business problems.
• Analyze large datasets to extract meaningful insights and drive data-informed decision-making.
• Collaborate with cross-functional teams to identify opportunities for leveraging AI and machine learning in various projects.
• Conduct experiments and validate models to ensure accuracy and reliability.
• Stay updated with the latest advancements in AI and machine learning technologies and apply them to improve existing processes.
• Mentor and guide junior data scientists and analysts in best practices and methodologies.
• Communicate findings and recommendations to stakeholders through clear and concise reports and presentations.

Mandatory Skills

• Proven experience in machine learning, including supervised and unsupervised learning techniques.
• Strong programming skills in Python, R, or similar languages.
• Expertise in data manipulation and analysis using libraries such as Pandas, NumPy, and Scikit-learn.
• Experience with deep learning frameworks such as TensorFlow or PyTorch.
• Solid understanding of statistical analysis and data visualization techniques.
• Ability to work with large datasets and distributed computing environments.

Preferred Skills

• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with big data technologies like Hadoop or Spark.