Data Analyst / Data Scientist

Role DescriptionWe are seeking a highly analytical, detail-oriented, and innovative Data Analyst / Data Scientist to transform complex data into actionable insights that support strategic decision-making and business growth. The successful candidate will be responsible for collecting, cleaning, analyzing, and interpreting large datasets, developing predictive models, creating visualizations, and collaborating with cross-functional teams to solve business challenges through data-driven solutions.The Data Analyst / Data Scientist will participate in the end-to-end data lifecycle, including data collection, preparation, analysis, modeling, visualization, and reporting. This role involves identifying trends, building statistical and machine learning models, developing dashboards, automating reporting processes, and delivering insights that improve operational efficiency and business performance.Key responsibilities include gathering and validating data from multiple sources, performing exploratory data analysis, creating reports and dashboards, developing predictive and statistical models, writing SQL queries, automating data workflows, and presenting findings to stakeholders. The role also involves collaborating with business teams, engineers, and management to define analytical requirements, improve data quality, optimize business processes, and support strategic initiatives through advanced analytics.The ideal candidate should possess strong analytical thinking, problem-solving abilities, and a passion for working with data. You will utilize modern analytics tools, programming languages, and visualization platforms to uncover meaningful insights and deliver scalable data solutions. Success in this position requires attention to detail, critical thinking, adaptability, continuous learning, and a commitment to delivering accurate, high-quality analytical outcomes.QualificationsBachelor's degree or higher in Data Science, Data Analytics, Statistics, Mathematics, Computer Science, Information Technology, Economics, Business Analytics, Engineering, or a related field.Strong understanding of data analysis, statistical methods, machine learning concepts, and data-driven decision-making.Proficiency in SQL for querying, extracting, transforming, and analyzing structured data.Experience with programming languages such as Python or R for data analysis, statistical modeling, and automation.Knowledge of data visualization tools such as Power BI, Tableau, Looker Studio, or similar business intelligence platforms.Familiarity with Microsoft Excel, including advanced formulas, PivotTables, charts, and data analysis functions.Understanding of data cleaning, preprocessing, validation, and data quality management techniques.Knowledge of statistical analysis, hypothesis testing, regression analysis, forecasting, clustering, and predictive modeling.Familiarity with machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, or similar frameworks is an advantage.Experience working with relational and non-relational databases such as MySQL, PostgreSQL, SQL Server, MongoDB, or similar platforms.Understanding of ETL processes, data pipelines, data warehousing, and business intelligence concepts.Familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform is considered an advantage.Ability to build dashboards, reports, and visualizations that communicate insights effectively to technical and non-technical stakeholders.Strong analytical, quantitative, and problem-solving skills with excellent attention to detail.Ability to interpret complex datasets, identify trends, and provide actionable business recommendations.Excellent written and verbal communication skills with the ability to present technical findings clearly.Ability to manage multiple projects, prioritize tasks, and meet deadlines in a fast-paced environment.Willingness to learn emerging technologies, analytical methodologies, and industry best practices.Ability to work independently while collaborating effectively with cross-functional teams.Strong commitment to data accuracy, continuous improvement, and delivering high-quality analytical solutions.