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Description:
Lead data science projects from problem formulation to model deployment.
Collaborate with cross-functional teams to identify business opportunities for data science projects.
Develop and implement machine learning algorithms and statistical models to solve complex business problems.
Conduct exploratory data analysis to uncover insights in large datasets.
Build and maintain scalable data pipelines with data engineers.
Evaluate and validate models using appropriate performance metrics.
Present findings and insights to stakeholders clearly and concisely.
Stay updated on the latest advancements in data science and machine learning.
Mentor and guide junior data scientists in the team.
Requirements:
Master's or PhD in Computer Science, Statistics, Mathematics, or related field.
Minimum 5 years of industry experience as a data scientist.
Proficient in Python or R for data analysis and modeling.
Strong knowledge and experience in machine learning, statistical modeling, and data mining.
Familiarity with big data technologies like Hadoop, Spark, or SQL.
Experience with deep learning frameworks like TensorFlow or PyTorch is a bonus.
Excellent problem-solving and critical-thinking skills.
Outstanding communication and presentation abilities.
Capable of working effectively in cross-functional teams.
Detail-oriented with the ability to manage multiple projects simultaneously.
Benefits:
Opportunity to lead and work on challenging data science projects.
Collaborate with diverse cross-functional teams to drive business impact.
Continuous learning and development in the field of data science and machine learning.
Mentorship and guidance provided to junior data scientists.