Chief AI Analytics Architect

6 days ago

Mumbai Kolkata Delhi, India beBeeMachineLearning Full time ₹ 12,00,000 - ₹ 30,00,000
Machine Learning Engineer Position

We are seeking a talented individual to join our team as a Machine Learning Engineer. The successful candidate will be responsible for designing and developing robust analytics models using statistical and machine learning algorithms. They will work closely with product and engineering teams to solve complex business problems, identify data-driven opportunities, and create personalized experiences for customers.

Key Responsibilities:
1. Analytics Model Development:
  • Analyze use cases and design appropriate analytics models using statistical and machine learning algorithms tailored to specific business requirements.
  • Develop machine learning algorithms to drive personalized customer experiences and provide actionable business insights.
  • Apply expertise in data mining and machine learning techniques, including forecasting, prediction, segmentation, recommendation, and fraud detection.

2. Data Engineering and Preparation:
  • Extend and augment company data with third-party data to enrich analytics capabilities.
  • Enhance data collection procedures to include necessary information for building analytics systems.
  • Prepare raw data for analysis, including cleaning, imputing missing values, and standardizing data formats using Python data frameworks (e.g., Pandas, NumPy).

3. Machine Learning Model Implementation:
  • Implement machine learning models, considering both performance and scalability using tools like PySpark in Databricks.
  • Design and build infrastructure to facilitate large-scale data analytics and experimentation.
  • Work with tools like Jupyter Notebooks for data exploration and model development.

The ideal candidate should have at least 5 years of experience in data analytics, with a strong understanding of core statistical algorithms such as classification and regression analysis. They should also have high-level knowledge of analytics use cases such as language analysis, assortment optimization, promotional planning, dynamic pricing, markdown optimization, labor scheduling, and optimization. Additionally, they should have proficiency in using analytics platforms like Databricks for large-scale data processing, and hands-on experience with data processing and analysis tools such as Pandas, NumPy, and Jupyter Notebooks.

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