Data Scientist

As a Data Scientist, your role involves analyzing large datasets, building predictive models, and generating actionable insights to support business decisions. You will collaborate with cross-functional teams to transform data into meaningful solutions in a fully remote setup. Key Responsibilities: - Collect, clean, and analyze structured and unstructured data - Build and deploy machine learning models - Perform data exploration and statistical analysis - Develop dashboards, reports, and data visualizations - Collaborate with product, engineering, and business teams - Communicate insights and recommendations to stakeholders - Optimize model performance and accuracy - Work with large datasets using scalable tools and techniques Qualification Required: - Strong programming skills in Python or R - Experience with data analysis libraries such as Pandas, NumPy, and Scikit-learn - Knowledge of machine learning algorithms - Strong understanding of statistics and probability - Experience with SQL and databases - Data visualization skills using tools like Power BI, Tableau, Matplotlib, and Seaborn - Problem-solving and analytical thinking In addition to the above requirements, the following skills are preferred: - Experience with deep learning frameworks like TensorFlow and PyTorch - Knowledge of big data tools such as Spark and Hadoop - Familiarity with cloud platforms like AWS, Azure, and GCP - Experience in NLP, computer vision, or recommendation systems - Understanding of MLOps and model deployment As a Data Scientist, your role involves analyzing large datasets, building predictive models, and generating actionable insights to support business decisions. You will collaborate with cross-functional teams to transform data into meaningful solutions in a fully remote setup. Key Responsibilities: - Collect, clean, and analyze structured and unstructured data - Build and deploy machine learning models - Perform data exploration and statistical analysis - Develop dashboards, reports, and data visualizations - Collaborate with product, engineering, and business teams - Communicate insights and recommendations to stakeholders - Optimize model performance and accuracy - Work with large datasets using scalable tools and techniques Qualification Required: - Strong programming skills in Python or R - Experience with data analysis libraries such as Pandas, NumPy, and Scikit-learn - Knowledge of machine learning algorithms - Strong understanding of statistics and probability - Experience with SQL and databases - Data visualization skills using tools like Power BI, Tableau, Matplotlib, and Seaborn - Problem-solving and analytical thinking In addition to the above requirements, the following skills are preferred: - Experience with deep learning frameworks like TensorFlow and PyTorch - Knowledge of big data tools such as Spark and Hadoop - Familiarity with cloud platforms like AWS, Azure, and GCP - Experience in NLP, computer vision, or recommendation systems - Understanding of MLOps and model deployment