Data Scientist/ ML Engineer

7 days ago

Delhi NCR New Delhi, India Sourceease Hr Services Full time US$ 1,50,000 - US$ 2,00,000 per year

Location: New Delhi, India

Duration: 6 Months (Extendable)

Experience Required: 6+ Years

Employment Type: Contract

About the Role

We are seeking a seasoned Machine Learning Engineer with a strong background in the BFSI (Banking, Financial Services, and Insurance) domain and expertise in time series forecasting and analysis. This is a contract-based opportunity for 6 months, with the potential for extension based on performance and project needs.

Youll be working on high-impact projects involving financial data modeling, predictive analytics, and scalable ML solutions that drive business decisions.

Key Responsibilities

  • Design, develop, and deploy ML models focused on time series forecasting for financial datasets.
  • Collaborate with data scientists, analysts, and business stakeholders to understand requirements and translate them into technical solutions.
  • Optimize and maintain existing ML pipelines for performance and scalability.
  • Conduct exploratory data analysis and feature engineering on large-scale structured and unstructured data.
  • Implement model validation, performance tracking, and continuous improvement strategies.
  • Document processes, models, and workflows for transparency and reproducibility.

Required Skills & Qualifications

  • Minimum 6 years of hands-on experience in machine learning and data science.
  • Proven experience in the BFSI domain, especially with financial time series data.
  • Strong proficiency in Python, R, or similar languages used for statistical modeling.
  • Experience with ML frameworks like TensorFlow, PyTorch, scikit-learn, etc.
  • Solid understanding of forecasting techniques such as ARIMA, Prophet, LSTM, and other deep learning approaches.
  • Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes) is a plus.
  • Excellent problem-solving and communication skills.

Preferred Qualifications

  • Master's or PhD in Computer Science, Statistics, Mathematics, or a related field.
  • Experience working with real-time data streams and financial risk modeling.
  • Exposure to MLOps practices and tools.

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