Data Scientist

This role is for one of the Weekday's clients

Requirements

Key Responsibilities

• Collect, clean, and analyze large and complex datasets to identify patterns, trends, and insights that inform business decisions
• Design, develop, and implement machine learning models, algorithms, and statistical techniques to solve real-world business problems
• Collaborate with stakeholders to translate business requirements into well-defined analytical solutions
• Create and maintain dashboards, reports, and visualizations that make insights easily understandable for non-technical stakeholders
• Perform exploratory data analysis (EDA) to generate hypotheses, test assumptions, and guide further analysis
• Continuously evaluate model performance and improve accuracy, scalability, and efficiency
• Partner with data engineering teams to ensure robust data pipelines and infrastructure for analytics and machine learning
• Communicate complex results in a clear and concise manner, tailoring the message for technical and non-technical audiences
• Stay updated with the latest advancements in machine learning, AI, and data science to bring innovative techniques to the organization
  

Required Skills And Qualifications

• 3-7 years of proven experience as a Data Scientist, preferably in a product-based or fast-paced environment
• Strong expertise in Python or R for data analysis, modeling, and scripting
• Hands-on experience with machine learning frameworks such as scikit-learn, TensorFlow, PyTorch, or similar
• Proficiency in SQL and working with relational as well as non-relational databases
• Strong statistical knowledge and experience applying hypothesis testing, regression, time-series forecasting, clustering, classification, and other advanced techniques
• Experience in building, deploying, and monitoring machine learning models in production environments
• Ability to design and deliver data visualizations using tools like Tableau, Power BI, or Python libraries (Matplotlib, Seaborn, Plotly)
• Familiarity with big data platforms such as Spark, Hadoop, or cloud-based solutions (AWS, GCP, or Azure) is a plus
• Excellent problem-solving skills with the ability to translate complex data into actionable strategies
• Strong communication and collaboration skills, with the ability to work effectively with diverse teams
  

Preferred Qualifications

• Exposure to Natural Language Processing (NLP), computer vision, or recommendation systems
• Experience with MLOps practices, version control (Git), and CI/CD pipelines for machine learning workflows
• Background in mathematics, statistics, computer science, data engineering, or a related field
• Experience in experimentation design, A/B testing, and causal inference