Data Scientist

Summary

Join our team as a skilled Data Scientist with 4+ years of experience. Leverage your expertise in data analysis, machine learning, and statistical modeling to extract actionable insights from complex datasets. Collaborate with cross-functional teams to solve business problems, develop predictive models, and contribute to data-driven decision-making. This role involves collecting, cleaning, and preprocessing data, designing and implementing machine learning models, performing EDA, building and validating predictive models, and communicating findings effectively. You will optimize existing models and stay current with industry trends. The ideal candidate will possess strong problem-solving and communication skills.

Requirements

• Hold a Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field
• Have 4+ years of professional experience as a Data Scientist or in a similar role
• Be proficient in programming languages such as Python or R for data analysis and modeling
• Possess strong experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
• Have expertise in statistical analysis, hypothesis testing, and experimental design
• Have hands-on experience with SQL for querying and manipulating large datasets
• Be familiar with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn)
• Have the ability to work in a collaborative environment and adapt to new AI technologies
• Possess excellent problem-solving skills and the ability to work independently or in a team
• Have strong communication skills to present complex findings in a clear and concise manner

Responsibilities

• Collect, clean, and preprocess large datasets from diverse sources to ensure data quality and integrity
• Design, develop, and implement machine learning models and algorithms to address business challenges
• Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies
• Build and validate predictive and prescriptive models using statistical techniques and tools
• Collaborate with stakeholders to translate business requirements into data-driven solutions
• Create visualizations and dashboards to communicate findings effectively to technical and non-technical audiences
• Optimize and fine-tune existing models to improve accuracy, performance, and scalability
• Stay current with industry trends, emerging tools, and advancements in data science and AI
• Document methodologies, processes, and results for reproducibility and knowledge sharing

Preferred Qualifications

• Have experience with cloud platforms (e.g., AWS, Azure, Google Cloud) for data processing and model deployment
• Have a background in natural language processing (NLP), computer vision, or time-series analysis
• Understand software development practices (e.g., version control with Git, CI/CD pipelines)