Data Scientist

Responsibilities:

Collaborate with stakeholders to understand business objectives and identify data-driven opportunities
Design and develop predictive models and machine learning algorithms to solve business problems
Clean, preprocess, and analyze large datasets using statistical techniques and machine learning tools
Develop data visualizations and dashboards to communicate insights and findings to stakeholders
Perform exploratory data analysis to uncover patterns, trends, and anomalies in data
Evaluate model performance and make recommendations for model improvements
Stay up-to-date with the latest advancements in data science and machine learning techniques
Work closely with engineers to deploy models into production and monitor their performance
Collaborate with cross-functional teams to integrate data science solutions into business processes
Participate in agile development processes, including sprint planning, daily stand-ups, and retrospectives

Requirements:

Master’s or Ph.D. degree in Computer Science, Statistics, Mathematics, Engineering, or related field
Proven experience as a Data Scientist or similar role
Proficiency in programming languages such as Python or R
Strong knowledge of machine learning techniques and algorithms (e.g., regression, classification, clustering, deep learning)
Experience with data visualization tools such as Tableau, Power BI, or matplotlib
Proficiency in SQL and experience working with relational databases (e.g., PostgreSQL, MySQL)
Familiarity with big data technologies such as Hadoop, Spark, or Kafka
Excellent problem-solving and analytical skills
Strong communication and presentation skills
Ability to work effectively in a fast-paced environment and collaborate with cross-functional teams
Fluency in English, both written and verbal
Preferred Qualifications:

Experience with cloud computing platforms such as AWS, Azure, or Google Cloud Platform
Knowledge of natural language processing (NLP) techniques and tools
Experience with distributed computing frameworks such as TensorFlow or PyTorch
Contributions to open-source projects or participation in data science competitions
Certifications in data science or machine learning (e.g., AWS Certified Machine Learning – Specialty, Google Professional Data Engineer)