Lead Data Scientist 5+ Years Experience

22 hours ago


Kozhikode, India PFACTORIAL TECHNOLOGIES PVT LTD Full time

Job Overview:

As a Data Scientist Engineer, you will play a critical role in developing and implementing advanced data science solutions to tackle complex business challenges and drive innovation within our organization. You will collaborate with cross-functional teams, lead machine learning projects, and mentor junior team members while staying at the forefront of emerging technologies in data science.


What You Will Do:

Machine Learning Model Development:

  • Design and implement robust machine learning models using statistical methods and classic ML algorithms (e.g., regression, decision trees, clustering).

Scalable ML Solutions:

  • Build and deploy scalable machine learning pipelines utilizing MLOps best practices to ensure consistency and efficiency across models and solutions.

Collaboration & Requirement Definition:

  • Collaborate with engineering, product management, and business stakeholders to identify opportunities and define specific requirements for data science projects.

Innovation & Experimentation:

  • Stay current with the latest advancements in data science, exploring new tools and techniques to continuously improve and enhance capabilities.

Mentorship & Leadership:

  • Provide technical mentorship to junior data science team members, fostering a culture of learning, growth, and innovation.

Research Application:

  • Apply cutting-edge research in data science and machine learning to real-world problems, pushing the boundaries of our solutions.

Communication & Stakeholder Engagement:

  • Communicate complex technical concepts and model results to non-technical stakeholders clearly and concisely, ensuring alignment on key decisions.


What We Are Looking For:

Experience & Skills:

  • 5+ years of experience in data science, with a strong focus on statistical machine learning and classic ML techniques.

Proficiency in Machine Learning:

  • Expertise in machine learning algorithms such as linear/logistic regression, decision trees, k-means clustering, random forests, and SVMs.

Programming & Tools:

  • Strong hands-on experience with Python (NumPy, Pandas, Scikit-learn) or other data science programming languages.

Advanced Technologies (Optional):

  • Familiarity with Generative AI models and Large Language Models (LLMs) (e.g., GPT, BERT) is a plus.
  • Experience with deep learning frameworks like TensorFlow and PyTorch is advantageous.

Data Preprocessing & Visualization:

  • Strong understanding of data preprocessing techniques, feature engineering, and data visualization tools to effectively manage and present data.

Big Data & Pipeline Design:

  • Proven experience in working with large datasets and designing efficient data pipelines for data processing and analysis.

Strong Problem-Solving & Communication:

  • Excellent analytical and problem-solving abilities.
  • Ability to clearly communicate complex data science concepts to non-technical stakeholders.

Mathematical & Statistical Foundation:

  • A strong foundation in mathematics and statistics, including probability, hypothesis testing, and optimization.




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