Job
Description
As a Data Scientist at our company, your role will involve analyzing our growing data, constructing data-driven solutions, and providing actionable insights to drive key business decisions and innovations across teams. Key Responsibilities: - Collect, clean, and preprocess structured/unstructured data from various sources - Analyze large datasets to identify trends, patterns, and insights that can inform strategic decisions - Develop and train predictive/statistical/machine-learning models to address business challenges - Create and implement data pipelines/ETL workflows as needed - Visualize and present findings through reports or dashboards for technical and non-technical stakeholders - Collaborate with product, engineering, and business teams to discover opportunities for data-driven features and solutions - Monitor and ensure the performance, reliability, and integrity of data models, especially those in production - Keep abreast of the latest advancements in data science/analytics/ML and apply relevant techniques Required Qualifications: - Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field - Proficiency in Python (or R), data manipulation libraries, and SQL (or equivalent database/querying tools) - Strong understanding of statistics, machine learning/modeling techniques, and data analysis principles - Experience working with extensive and intricate datasets, including data cleaning and preprocessing - Analytical mindset, strong problem-solving capabilities, and attention to detail - Effective communication skills to translate technical findings into actionable business insights - Ability to collaborate effectively with cross-functional teams Preferred / Nice-to-have: - Familiarity with data visualization tools (e.g., Tableau, Power BI, or equivalent) or Python/R visualization libraries - Experience with Big Data tools (e.g., Spark/Hadoop) and managing large-scale data pipelines - Exposure to cloud computing platforms (e.g., AWS, GCP, Azure) for data processing or storage - Experience in deploying ML models or working in a production environment - Basic understanding of data engineering practices such as ETL, data warehousing, and pipelines Job Type: Full-time Work Location: In person As a Data Scientist at our company, your role will involve analyzing our growing data, constructing data-driven solutions, and providing actionable insights to drive key business decisions and innovations across teams. Key Responsibilities: - Collect, clean, and preprocess structured/unstructured data from various sources - Analyze large datasets to identify trends, patterns, and insights that can inform strategic decisions - Develop and train predictive/statistical/machine-learning models to address business challenges - Create and implement data pipelines/ETL workflows as needed - Visualize and present findings through reports or dashboards for technical and non-technical stakeholders - Collaborate with product, engineering, and business teams to discover opportunities for data-driven features and solutions - Monitor and ensure the performance, reliability, and integrity of data models, especially those in production - Keep abreast of the latest advancements in data science/analytics/ML and apply relevant techniques Required Qualifications: - Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field - Proficiency in Python (or R), data manipulation libraries, and SQL (or equivalent database/querying tools) - Strong understanding of statistics, machine learning/modeling techniques, and data analysis principles - Experience working with extensive and intricate datasets, including data cleaning and preprocessing - Analytical mindset, strong problem-solving capabilities, and attention to detail - Effective communication skills to translate technical findings into actionable business insights - Ability to collaborate effectively with cross-functional teams Preferred / Nice-to-have: - Familiarity with data visualization tools (e.g., Tableau, Power BI, or equivalent) or Python/R visualization libraries - Experience with Big Data tools (e.g., Spark/Hadoop) and managing large-scale data pipelines - Exposure to cloud computing platforms (e.g., AWS, GCP, Azure) for data processing or storage - Experience in deploying ML models or working in a production environment - Basic understanding of data engineering practices such as ETL, data warehousing, and pipelines Job Type: Full-time Work Location: In person
