Machine Learning Engineer

5 days ago

Agra, Uttar Pradesh, India beBeeDataScientist Full time US$ 1,50,000 - US$ 1,90,000

Key Responsibilities

  • Collaborate with clients to understand their business objectives and challenges, providing data-driven recommendations and AI/ML solutions that enhance decision-making and deliver tangible value.
  • Translate business needs - particularly within financial services domains such as marketing, risk, compliance and customer lifecycle management into well-defined machine learning problem statements and solution workflows.
  • Use analytics and machine learning techniques: Conduct exploratory data analysis, feature engineering, and model development to uncover insights and predict outcomes.
  • Develop and deploy ML models, including supervised and unsupervised learning algorithms and model performance optimization.
  • Design and implement scalable, cloud-native ML pipelines and APIs using tools like Python, Scikit-learn, TensorFlow, and PyTorch.
  • Work with cross-functional teams to deliver robust and reliable solutions in cloud environments such as AWS, Azure, or GCP.
  • Communicate complex technical information to various stakeholders at various stages of engagement such as pre-sales, sales, and delivery using data-driven insights.
  • Stay current with developments in AI, ML modelling, and data engineering best practices, and integrate them into project work.
  • Mentor junior team members, provide guidance on modelling practices, and contribute to an environment of continuous learning and improvement.

Job Requirements

  • 4 to 7 years of relevant experience in building ML solutions, with a strong foundation in machine learning modelling and deployment.
  • Strong exposure to banking, payments, fintech or Wealth/Asset management domains, with experience working on problems related to:
  • Marketing analytics for product cross-sell/up-sell and campaign optimization
  • Customer churn and retention analysis
  • Credit risk assessment and scoring models
  • Fraud detection and transaction risk modeling
  • Customer segmentation for personalized targeting
  • Experience in developing traditional ML models across business functions such as risk, marketing, customer segmentation, and forecasting.
  • Bachelor's or Master's degree from a Tier 1 technical institute or MBA from Tier 1 institute
  • Proficiency in Python and experience with AI/ML libraries such as Scikit-learn, TensorFlow, PyTorch.
  • Experience in end-to-end model development lifecycle: data preparation, feature engineering, model selection, validation, deployment, and monitoring.
  • Eagerness to learn and familiarity with developments in Agentic AI space
  • Strong problem-solving capabilities and the ability to independently lead tasks or contribute within a team setting
  • Effective communication and presentation skills for internal and client-facing interactions
  • Ability to bridge technical solutions with business impact and drive value through data science initiatives

Benefits

This is a challenging and rewarding role that offers opportunities for professional growth and development. If you are a motivated and experienced data scientist looking for a new challenge, we encourage you to apply.

How to Apply

Please submit your resume and cover letter to apply for this position.

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