Data Scientist

2 days ago

Bengaluru, Karnataka, India beBeeData Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Data Science Leader

We are seeking an experienced professional to lead our team of data engineers, analysts, and scientists in delivering innovative solutions.

  • A graduate degree in a quantitative field (computer science, statistics, applied mathematics, machine learning, or related discipline) is essential for success.

The ideal candidate will have:

  • Strong programming skills in Python with expertise in Python's numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, etc.
  • Experience with Large Language Models (LMs) like Llama, T5, Falcon, Langchain, or similar frameworks is highly desirable.
  • A deep understanding of the evolution history of NLP, training data creation, training set-up, and finetuning is required.
  • The ability to interpret research papers and architecture diagrams of Language Models is crucial.
  • Familiarity with LORA, RAG, Instruct fine-tuning, Quantization, etc. is a plus.
  • Predictive modeling experience in Python (Time Series/ Multivariable/ Causal)
  • Experience applying various machine learning techniques and understanding the key parameters that affect their performance.
  • Experience of building systems that capture and utilize large data sets to quantify performance via metrics or KPIs.
  • Excellent verbal and written communication skills.
  • Able to work in a dynamic, fast-paced, innovative environment with several ongoing concurrent projects.

Key Responsibilities:

  • Lead a team of data engineers, analysts, and data scientists to carry out activities such as:
  • Collaborating with internal/external stakeholders to understand business requirements.
  • Coordinating with relevant stakeholders to gather relevant data artifacts, anecdotes, and hypothesis.
  • Creating project plans and sprints for milestones/deliverables.
  • Optimizing clusters for data science workflows.
  • Creating data pipelines to ingest data effectively.
  • Ensuring the quality of data with proactive checks and resolving gaps.
  • Carrying out EDA, feature engineering, and defining performance metrics prior to running relevant ML/DL algorithms.
  • Researching whether similar solutions have been already developed before building ML models.
  • Creating optimized data models to query relevant data efficiently.
  • Running relevant ML/DL algorithms for business goal seek.
  • Validating these ML/DL models to scale.
  • Creating light applications, simulators, and scenario builders to help business consume end outputs.
  • Testing codes pre-production for possible bugs and resolving these bugs proactively.
  • Integrating and operationalizing models in client ecosystem.
  • Documenting project artifacts and logging failures and exceptions.
  • Measuring impact of DS projects on business metrics, and finetuning workflow based on feedbacks.

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