Senior Data Scientist - Machine Learning/Deep Learning (6-8 yrs)

Responsibilities :

- Collect, clean, and prepare large and complex datasets from various sources (databases, APIs, cloud platforms).

- Perform data exploration and analysis to identify patterns, trends, and anomalies.

- Ensure data quality and integrity.

- Develop and implement predictive models using machine learning algorithms (regression, classification, clustering, time series analysis).

- Conduct A/B testing and other statistical analyses to evaluate model performance.

- Explore and implement advanced machine learning techniques (deep learning, natural language processing).

- Create insightful and compelling data visualizations (dashboards, charts, graphs) to communicate findings effectively.

- Prepare and present data-driven reports and presentations to stakeholders.

- Translate complex technical concepts into clear and concise business language.

- Translate data insights into actionable business recommendations.

- Collaborate with business stakeholders to define and measure key performance indicators (KPIs).

- Identify opportunities to improve business processes and increase efficiency through data-driven solutions.

- Stay up-to-date with the latest advancements in data science and machine learning.

- Explore and evaluate new technologies and techniques to address business challenges.

- Conduct research and experimentation to develop innovative data solutions.

- Collaborate effectively with data engineers, data analysts, and other cross-functional teams.

- Mentor junior data scientists and provide guidance on data science best practices.

Qualifications :

- Master's degree in Statistics, Computer Science, or a related field.

- 5+ years of hands-on experience in data science, with a strong focus on statistical modeling and machine learning.

- Proficiency in Python and its data science libraries (pandas, NumPy, Scikit-learn).

- Experience with data visualization libraries (Matplotlib, Seaborn, Tableau).

- Strong understanding of statistical concepts and methodologies.

- Experience with cloud platforms (AWS, Azure, GCP) is a plus.

- Experience with big data technologies (Hadoop, Spark) is a plus.

- Excellent analytical and problem-solving skills.

- Strong communication and presentation skills.

- Ability to work independently and as part of a team.

Bonus Points :

- Experience with deep learning frameworks (TensorFlow, PyTorch).

- Experience with natural language processing (NLP) techniques.

- Experience with time series analysis.

- Experience with data engineering and data pipeline development.

- Publications in relevant academic journals or conferences