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Senior Data Scientist

2 months ago

Gurugram, India Mrikal Full time

About Mrikal: Mrikal is a leading product studio specializing in digital solutions across Pharma, Retail, Oil & Gas, and Edtech industries. Our multidisciplinary team excels in design, development, deployments, data engineering, and AI. We are committed to delivering world-class solutions through good architecture, data practices, embedded AI, user empathy, and growth hacks.


About the Role:

We are seeking a highly skilled Senior Data Scientist to join our team and drive the implementation of cutting-edge AI solutions in Risk Modelling and machine learning. The ideal candidate will have extensive experience in developing and deploying advanced AI models and techniques.


Key Responsibilities:

  • Lead the data science lifecycle, including data acquisition, cleaning, exploration,

feature engineering, and model training.

  • Develop and implement robust machine learning pipelines incorporating AI/ML and

Deep learning techniques, applying best practices for data pre-processing, model

selection, training, and evaluation for assessing creditworthiness and fraud potential.

  • Developing risk models: Creating ML models to evaluate financial risks associated

with lending or other financial activities.

  • Scoring algorithms: Designing and developing ML models to assess creditworthiness

or segment customers based on various factors.

  • Continuously monitor and evaluate model performance, identifying areas for

improvement and retraining as necessary.

  • Collaborate with engineers to integrate machine learning models into production

environments and ensure efficient deployment.

  • Stay current on the latest advancements in AI/ML and Generative AI by actively

researching new techniques and participating in training opportunities..


Requirements:

  • 5+ years of experience in applied data science with a focus on machine learning

and financial modeling..

  • Experience with financial risk modeling or telecom scoring modeling. Knowledge of

credit risk assessment, fraud detection, or customer churn prediction

  • Proven track record of successfully designing, developing, and deploying machine
  • learning models in production environments.
  • Strong understanding of machine learning principles, algorithms, and frameworks

(e.g., scikit-learn, TensorFlow, PyTorch).

  • Proficiency in programming languages like Python, R, or Scala and familiarity with

data wrangling libraries (e.g., pandas).

  • Experience with cloud platforms (e.g., AWS, GCP, Azure) for data storage,

processing, and model deployment (a plus).

  • Strong communication and collaboration skills with the ability to explain complex

technical concepts to business.

  • A critical thinker with a problem-solving mindset and a passion for exploring new data

science and AI/ML techniques.