Lead Data Scientist

Job Title:

Location:

About the Role:

Lead Data Scientist

Key Responsibilities:

• Lead the development of machine learning models and algorithms to solve complex business problems.
• Analyze large and complex data sets to identify trends, patterns, and insights.
• Collaborate with engineering teams to deploy data science solutions into production environments.
• Design and implement data pipelines to ensure the availability and quality of data for analysis.
• Work with business stakeholders to understand their requirements and translate them into data science solutions.
• Conduct exploratory data analysis, feature engineering, and model evaluation.
• Communicate findings and insights effectively to both technical and non-technical audiences.
• Stay updated with the latest industry trends and technologies in data science and machine learning.
• Mentor and guide junior data scientists and analysts.

Qualifications:

• Master's or Ph.D. degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
• 8+ years of experience in data science, machine learning, or a related field.
• Strong programming skills in Python or R, with experience in data manipulation and analysis using libraries such as pandas, NumPy, scikit-learn, TensorFlow, or PyTorch.
• Proficiency in SQL and experience with database management systems.
• Proven experience in building and deploying machine learning models in production.
• Strong understanding of statistical analysis, hypothesis testing, and data modeling techniques.
• Experience with big data technologies such as Hadoop, Spark, or similar.
• Excellent problem-solving skills and attention to detail.
• Strong communication skills, with the ability to explain complex technical concepts to a non-technical audience.
• Experience with data visualization tools such as Tableau, Power BI, or similar.

Preferred Qualifications:

• Experience in the [specific industry, e.g., finance, healthcare, e-commerce, etc.].
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with deep learning techniques and frameworks.
• Experience with natural language processing (NLP) or computer vision is a plus.

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