Data Scientist - Machine Learning/Artificial Intelligence (7-14 yrs)

You Will :

- Lead the design, development, and deployment of machine learning models and AI solutions that address key business challenges.

- Architect and manage large-scale data systems to process, analyze, and extract insights from massive datasets (terabytes or more).

- Collaborate closely with cross-functional teams, including Product, Engineering, and Business Intelligence, to develop data-driven strategies and solutions.

- Drive data science best practices and mentor junior and mid-level data scientists, ensuring they are aligned with cutting-edge methodologies.

- Communicate complex technical findings to both technical and non-technical stakeholders, offering clear insights that influence business decisions.

- Stay ahead of the latest advancements in AI/ML and data science, identifying new opportunities for the company to innovate.

- Ensure the scalability, efficiency, and security of all data-driven initiatives by optimizing algorithms and infrastructure.

You'll Have :

- A PhD or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.

- 7-15 years of hands-on experience in data science, machine learning, and advanced analytics.

- Proven expertise in building and deploying machine learning models, deep learning frameworks, and advanced statistical techniques.

- Strong proficiency in programming languages such as Python, R, and expertise in machine learning libraries (e.g., TensorFlow, Scikit-Learn, PyTorch).

- Extensive experience managing and analyzing large datasets using big data tools (e.g., Spark, Dask, Ray) and distributed computing environments.

- A strong track record of working with leadership to drive AI strategy and influence business decisions using data insights.

- Excellent communication skills and the ability to present complex data science concepts in a clear and concise manner.

Preferred Qualifications :

- Experience with real-time data processing, streaming technologies, and cloud platforms (AWS, GCP, Azure).

- Prior experience working with cybersecurity data or an interest in the domain.

- Expertise in data visualization and graphing techniques to represent complex data.

- Familiarity with compiled languages (e.g., C++, Java) and experience with low-resource system deployments.

- Experience leading data science teams and projects from concept to implementation