Lead and assist in building advanced machine learning models, predictive analytics, and statistical methods to address various business challenges.
Showcase expertise in programming languages like Python or R, with a focus on writing clear, efficient, and maintainable code. Experience with key libraries and frameworks (such as TensorFlow, PyTorch, and scikit-learn) is critical.
Utilize strong problem-solving abilities to create data-driven solutions, analyze complex datasets, and extract actionable insights that drive meaningful results.
Collaborate closely with clients to comprehend their business goals, identify opportunities for advanced analytics-driven strategies, and communicate results effectively and in a timely manner.
Manage the entire model development lifecycle, from defining the problem and exploring data to training, validating, and deploying models.
Work alongside cross-functional teams, including data engineers, software developers, ML-Ops Engineer and business stakeholders, to integrate analytics solutions into business operations.
Apply a deep understanding of mathematical and statistical concepts to guide the development and validation of advanced data science models.
Desired Skills and Experience:
5-8 years of comprehensive experience in data science and model development.
Experience in Machine learning Framework like TensorFlow, PyTorch, and scikit-learn etc
Good to have hands on experience in Data & AI platforms like Databricks,AWS SageMaker etc
Demonstrate a strong passion for writing high-quality Python code, ensuring it is modular, scalable, and suitable for end-to-end project execution, with active involvement in planning and hands-on work.
Extensive knowledge of regression and classification techniques, along with the mathematical principles behind them, and proficiency in SQL.
In-depth understanding of a wide range of data science methodologies, machine learning algorithms, and statistical techniques.
Excellent communication skills, with the ability to present clearly, articulate ideas, tell compelling data stories, and navigate complex client situations.
Provide effective mentorship to team members, leveraging expertise in relevant industry, domain, or functional areas
