Our client, an innovative technology company at the forefront of data-driven decision making, is seeking a talented and motivated Data Scientist to join their growing analytics team. This role offers an exciting opportunity to leverage advanced analytics and machine learning to solve complex business problems and drive strategic initiatives.
Responsibilities:
- Collect, process, and analyze large datasets from various sources to extract meaningful insights
- Develop and implement advanced statistical models and machine learning algorithms to solve complex business problems
- Create and maintain scalable data pipelines to support analytics and machine learning projects
- Collaborate with cross-functional teams to identify opportunities for data-driven solutions
- Design and conduct A/B tests to evaluate the effectiveness of different strategies
- Develop predictive models to forecast trends and support decision-making processes
- Communicate findings and recommendations to both technical and non-technical stakeholders through compelling visualizations and presentations
- Stay current with the latest advancements in data science, machine learning, and artificial intelligence
- Contribute to the development of best practices and methodologies for the data science team
- Mentor junior data scientists and analysts, fostering a culture of knowledge sharing and innovation
Requirements:
- Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field
- 3+ years of hands-on experience in data science or a related role
- Strong proficiency in Python or R, and experience with SQL
- Expertise in machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
- Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (AWS, Azure, or GCP)
- Solid understanding of statistical analysis, experimental design, and causal inference
- Proficiency in data visualization tools (e.g., Tableau, PowerBI, or matplotlib)
- Excellent problem-solving skills and ability to translate complex problems into analytical frameworks
- Strong communication skills, able to explain technical concepts to non-technical audiences
- Experience in one or more domain areas such as marketing analytics, financial modeling, or customer behavior analysis is a plus
Responsibilities:
- Collect, process, and analyze large datasets from various sources to extract meaningful insights
- Develop and implement advanced statistical models and machine learning algorithms to solve complex business problems
- Create and maintain scalable data pipelines to support analytics and machine learning projects
- Collaborate with cross-functional teams to identify opportunities for data-driven solutions
- Design and conduct A/B tests to evaluate the effectiveness of different strategies
- Develop predictive models to forecast trends and support decision-making processes
- Communicate findings and recommendations to both technical and non-technical stakeholders through compelling visualizations and presentations
- Stay current with the latest advancements in data science, machine learning, and artificial intelligence
- Contribute to the development of best practices and methodologies for the data science team
- Mentor junior data scientists and analysts, fostering a culture of knowledge sharing and innovationRequirements:
- Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field
- 3+ years of hands-on experience in data science or a related role
- Strong proficiency in Python or R, and experience with SQL
- Expertise in machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
- Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (AWS, Azure, or GCP)
- Solid understanding of statistical analysis, experimental design, and causal inference
- Proficiency in data visualization tools (e.g., Tableau, PowerBI, or matplotlib)
- Excellent problem-solving skills and ability to translate complex problems into analytical frameworks
- Strong communication skills, able to explain technical concepts to non-technical audiences
- Experience in one or more domain areas such as marketing analytics, financial modeling, or customer behavior analysis is a plus