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Job Description

Lead Data Scientist

We are looking for 8+years experienced candidates for this role.

  • A minimum of 8 years of professional experience, with at least 6 years in a data science role.
  • Strong knowledge of statistical modeling, machine learning, deep learning and GenAI.
  • Proficiency in Python and hands on experience optimizing code for performance.
  • Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning.
  • Solid understanding of database concepts and experience working with large datasets.
  • Experience deploying and scaling machine learning models in a production environment.
  • Familiarity with machine learning operations (MLOps) and related tools.
  • Good understanding of Generative AI concepts and LLM finetuning.
  • Excellent communication and collaboration skills.

Responsibilities include:

  • Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities.
  • Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions.
  • Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance.
  • Lead the development and deployment of machine learning/deep learning models to address key business challenges.
  • Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models.
  • Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems.
  • Design, implement, and optimize data pipelines for model training and deployment.
  • Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar).
  • Design and implement APIs for model serving and integration with other systems.
  • Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results.
  • Mentor junior data scientists, providing guidance on technical skills and project execution.
  • Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications.
  • Communicate complex technical concepts and analytical findings to both technical and non-technical audiences.
  • Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work

Certifications

  • Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area.

Primary Skills :

  • Python
  • Data Science concepts
  • Pandas, NumPy, Matplotlib
  • Artificial Intelligence
  • Statistical Modeling
  • Machine Learning, Natural Language Processing (NLP), Deep Learning
  • Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe)
  • MLOps(e.g; MLflow, Tensorboard, Kubeflow etc)
  • Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly
  • Detection, Recommendation Systems (Atleast 2)
  • Generative AI, RAG, Finetuning(LoRa, QLoRa)
  • Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP)

Secondary Skills :

  • Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions.
  • Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals.
  • Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

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