Data Analytics Lead

Job Description

Technical skills include programming Python R SQL statistical analysis machine learning data visualization and experience with big data tools. Soft skills include analytical thinking communication problem solving and teamwork Programming Proficiency in languages like Python R and SQL is essential for data manipulation analysis and model building Statistics and Probability A strong foundation in statistical analysis and probability is needed to understand and interpret data as well as develop machine learning models Machine Learning Understanding and applying various machine learning algorithms and techniques is crucial for building predictive models Data Visualization The ability to create effective visualizations that communicate insights from data is vital for presenting findings and making datadriven decisions Data Wrangling and Database Management Skills in cleaning transforming and managing data often using SQL or other database systems are essential for preparing data for analysis Cloud Computing Familiarity with cloud platforms like AWS Azure or Google Cloud and the ability to leverage them for data storage processing and analysis is becoming increasingly important Natural Language Processing NLP For working with text data understanding NLP techniques is beneficial Big Data Knowledge of big data technologies like Hadoop and Spark is helpful for handling large datasets Soft Skills Communication The ability to effectively communicate complex data insights to both technical and nontechnical audiences is crucial Critical Thinking The ability to analyze problems identify solutions and evaluate results is essential for datadriven decisionmaking Problem Solving Data scientists need to be able to identify problems develop solutions and implement them effectively Business Acumen Understanding the business context and how data can be used to drive business outcomes is important Teamwork Data scientists often work in teams so collaboration and communication skills are important