Data Scientist

Responsibilities:

• Identify, collect, and clean data from various sources (e.g., databases, APIs, web scraping).
• Develop and implement data preprocessing techniques, including data cleaning, transformation, and feature engineering.
• Ensure data quality, integrity, and security.
• Explore and analyze large datasets to uncover trends, patterns, and insights.
• Develop and implement statistical models and machine learning algorithms (e.g., regression, classification, clustering, time series analysis, deep learning).
• Evaluate model performance using appropriate metrics and iterate to improve accuracy and effectiveness.
• Experiment with different algorithms and techniques to find the most suitable solutions for specific business problems.
• Create compelling data visualizations (e.g., charts, graphs, dashboards) to communicate findings effectively.
• Develop and present clear and concise reports and presentations to both technical and non-technical audiences.
• Translate complex data insights into actionable recommendations.
• Work closely with cross-functional teams (e.g., product, engineering, marketing) to understand business needs and translate them into data science projects.
• Communicate effectively with stakeholders to understand requirements, provide updates, and present findings.
• Participate in team meetings and contribute to a collaborative remote work environment.
• Stay up-to-date with the latest advancements in data science, machine learning, and related technologies.
• Proactively identify opportunities to leverage data science to solve new business challenges and improve existing processes.
• Experiment with new tools and techniques to enhance the team’s capabilities.
• Collaborate with engineering teams to deploy models and data pipelines into production.
• Develop monitoring systems to track model performance and data quality over time.
• Troubleshoot and resolve issues related to deployed models and data infrastructure.

Qualifications:

Education: Bachelor’s or Master’s degree in a quantitative field such as  Computer Science, Statistics, Mathematics, Economics, or a related discipline. A Ph.D. is a plus for more research-oriented roles.

Experience: Proven experience 3+ years working as a Data Scientist or in a similar analytical role.

Technical Skills:

• Strong proficiency in programming languages such as Python and/or R.
• Experience with relevant data science libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch, pandas, NumPy, matplotlib, seaborn).
• Solid understanding of statistical modeling, machine learning algorithms, and their underlying principles.
• Experience with database systems (e.g., SQL, NoSQL) and data warehousing concepts.
• Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and their data science services is a plus.
• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn).
• Knowledge of data engineering principles and tools is a plus.

Soft Skills:

• Excellent problem-solving and analytical skills.
• Strong communication and presentation skills, with the ability to explain complex technical concepts to non-technical audiences.
• Ability to work independently and manage time effectively in a remote environment.
• Strong collaboration and teamwork skills.
• A proactive and results-oriented mindset.
• Strong attention to detail and a commitment to data quality.