Pfactorial technologies pvt ltd | lead data scientist 5+ years experience

1 month 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 (Num Py, 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 Tensor Flow and Py Torch 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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