Senior Data Science Specialist

1 day ago

Udaipur, Rajasthan, India beBeeMachineLearning Full time ₹ 20,00,000 - ₹ 25,00,000

Job Title: Machine Learning Engineer

 

  • About the Role:
  • This is an exciting opportunity to leverage your expertise in machine learning and AI to drive business growth.
  • You will be responsible for developing innovative solutions using cutting-edge techniques such as GEN AI, deep learning, and machine learning.

 

Key Responsibilities:

  • Strategic Problem Solving: Develop and implement data-driven solutions to complex problems using machine learning and AI techniques.
  • Team Leadership: Lead a team of data scientists to deliver high-quality project results on time.
  • Client Needs Analysis: Analyze client needs and identify opportunities to apply machine learning and AI techniques.
  • Feature Selection and Model Building: Select features, build, and optimize classifiers/regressors using machine learning and deep learning techniques.
  • Data Collection and Quality Assurance: Enhance data collection procedures to ensure data accuracy and quality.
  • Ad-Hoc Analysis and Communication: Perform ad-hoc analysis and present results clearly to technical and non-technical stakeholders.
  • Custom Reporting and Presentation: Create custom reports and presentations with strong data visualization and storytelling skills.
  • Expertise and Skills: Expertise in machine learning, AI, and deep learning techniques. Strong programming skills in Python.

 

Requirements:

  • Primary Skills:
  • Excellent understanding and hands-on experience in machine learning and AI techniques & algorithms for supervised & unsupervised problems, NLP, computer vision, and GEN AI.
  • Proficient in coding in common data science languages & tools such as R, Python.
  • Experience with common data science toolkits, such as NumPy, Pandas, Matplotlib, StatsModel, Scikitlearn, SciPy, NLTK, Spacy, OpenCV, etc.
  • Experience with common data science frameworks such as Tensorflow, Keras, PyTorch, XGBoost, etc.
  • Exposure or knowledge in cloud (Azure/AWS).
  • Experience in deploying models in production.

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