Senior Data Scientist

Job Brief:
We are seeking a highly skilled Data Scientist to join our dynamic team. The ideal candidate will have a strong background in data analysis, machine learning, and statistical modeling. You will be responsible for analyzing large datasets to uncover trends and insights, building predictive models, and contributing to data-driven decision-making processes.

Duties and Responsibilities:

• Lead the development and execution of data science projects, including problem formulation, data collection, analysis, modeling, and deployment of machine learning models.
• Collaborate with cross-functional teams to identify business opportunities and translate them into data science projects.
• Develop and implement machine learning algorithms and statistical models to solve complex business problems.
• Perform exploratory data analysis to gain insights and identify patterns in large and complex datasets.
• Work with data engineers to build robust and scalable data pipelines.
• Evaluate and validate models using appropriate performance metrics and statistical techniques.
• Present findings and insights to stakeholders in a clear and concise manner.
• Stay up-to-date with the latest advancements and best practices in data science and machine learning.
• Mentor and guide more junior data scientists in the team.

Requirements

• Bachelors in Computer Science, Statistics, Mathematics, or a related field.
• Minimum of 5 years of industry experience as a data scientist.
• Strong knowledge and experience in machine learning, statistical modeling, and data mining.
• Proficiency in Python or R for data analysis and modeling.
• Experience with big data technologies such as Hadoop, Spark, or SQL.
• Experience with deep learning frameworks such as TensorFlow or PyTorch is a plus.
• Strong problem-solving and critical-thinking skills.
• Excellent communication and presentation skills.
• Ability to work effectively in cross-functional teams.
• Strong attention to detail and ability to work on multiple projects simultaneously.

Originally posted on Himalayas