Data Scientist

As a Data Scientist at Bright Vision Technologies, you will be responsible for analyzing complex datasets, developing statistical models, and applying machine learning algorithms to extract valuable insights and solve challenging business problems. You will collaborate with cross-functional teams to identify data-driven opportunities, develop predictive models, and drive the implementation of data-driven solutions.

Responsibilities:
Analyze large and complex datasets to identify patterns, trends, and insights
Develop statistical models and machine learning algorithms to solve business problems
Collaborate with cross-functional teams to understand project requirements and deliver data-driven solutions
Apply data cleaning, preprocessing, and feature engineering techniques
Evaluate and validate models performance and accuracy
Communicate findings and insights to technical and non-technical stakeholders
Stay up-to-date with the latest trends, algorithms, and advancements in data science and machine learning
Continuously improve data science methodologies and processes within the organization

Requirements:
Proven experience as a Data Scientist or similar role
Strong proficiency in programming languages such as Python or R
Solid understanding of statistics and mathematical concepts relevant to data science
Experience with data visualization and reporting tools
Knowledge of machine learning algorithms and techniques
Familiarity with data manipulation and analysis using SQL
Strong problem-solving and analytical skills
Excellent communication and presentation skills
Ability to work in a fast-paced and collaborative environment

Preferred Qualifications:
Masters or Ph.D. degree in Data Science, Computer Science, Statistics, or a related field
Experience with deep learning frameworks, such as TensorFlow or PyTorch
Knowledge of big data processing technologies (e.g., Hadoop, Spark)
Familiarity with cloud-based data platforms (e.g., AWS, Azure, Google Cloud Platform)
Experience with data engineering and data preprocessing techniques
Publications or contributions to the data science community (e.g., research papers, open-source projects)