Senior Data Scientist - Python/PySpark (6-10 yrs)

Position : Senior Data Scientist

Experience : 6 years

Required Skills :

- TensorFlow

- PyTorch

- Pandas

- AI/ML

- Python

- MLops

- PySpark

- Azure

Key Responsibilities :

Data Analysis & Modeling : Apply advanced statistical methods, machine learning algorithms, and predictive modeling techniques to solve complex business problems.

Collaborate with Teams : Work closely with cross-functional teams, including business analysts, engineers, and product managers, to understand business needs and provide data-driven solutions.

Data Engineering : Assist in the design and optimization of data pipelines to ensure the availability and accuracy of data for analysis and modeling.

Model Deployment : Lead the deployment of machine learning models and algorithms into production environments, ensuring scalability and maintainability.

Data Visualization & Reporting : Create clear, actionable reports and visualizations to communicate findings to stakeholders across different departments.

Mentorship : Mentor and guide junior data scientists and analysts, providing advice on best practices and complex technical issues.

Research & Innovation : Stay up-to-date with the latest research in data science and machine learning, identifying opportunities for new techniques and technologies that could benefit the organization.

Qualifications :

- Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a related field (Ph.D. preferred).

- 5+ years of experience in data science, analytics, or machine learning.

- Strong proficiency in programming languages such as Python, R, or Scala.

- Expertise in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn, XGBoost).

- Experience with SQL and working with large-scale databases (e.g., MySQL, PostgreSQL, NoSQL).

- Advanced knowledge of statistical analysis and modeling (e.g., hypothesis testing, regression,

classification, clustering).

- Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data tools (e.g., Hadoop, Spark) is a plus.

- Strong communication skills with the ability to explain complex technical concepts to non-technical stakeholders.

- Ability to work independently and in teams, with strong problem-solving and analytical skills.

Preferred Skills :

- Experience in industry-specific data science applications (e.g., finance, healthcare, e-commerce).

- Familiarity with data visualization tools (e.g., Tableau, Power BI, D3.js).

- Experience with deploying models in production environments using tools like Docker, Kubernetes, or

cloud-native services.

- Knowledge of deep learning and natural language processing (NLP) techniques is a plus.