Data Scientist III (IT)
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Role details
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Job description
The Data Scientist III is responsible for applying advanced data analysis techniques and the scientific method to solve complex business and technical problems. This role requires strong expertise in statistics, machine learning, and programming, with the ability to transform raw data into actionable insights., * Apply the scientific method to frame problems, test hypotheses, and validate results
- Perform data wrangling, cleansing, and preprocessing on structured and unstructured datasets
- Conduct exploratory data analysis (EDA) to identify trends, patterns, and anomalies
- Build, evaluate, and deploy statistical and machine learning models
- Apply a variety of machine learning algorithms (e.g., regression, classification, clustering, ensemble methods)
- Work with large-scale datasets and big data processing frameworks
- Create data visualizations and dashboards to communicate insights effectively
- Collaborate with cross-functional teams including IT, data engineering, analytics, and business stakeholders
- Translate complex analytical findings into clear, actionable recommendations
- Document methodologies, models, assumptions, and results
Requirements
The ideal candidate has hands-on experience with data wrangling, exploratory data analysis, statistical modeling, machine learning algorithms, and data visualization, and can work effectively with large and complex datasets in an enterprise IT environment., * 5-10 years of experience in data science, analytics, or a related role
- Strong proficiency in statistics and probability
- Proficiency in at least one programming language:
- Python or
- R
- Hands-on experience with data wrangling, analysis, and exploration
- Familiarity with a wide range of machine learning algorithms
- Experience creating data visualizations using industry-standard tools or libraries
- Strong analytical, problem-solving, and critical-thinking skills
- Excellent written and verbal communication abilities
Preferred Qualifications
- Experience with big data processing frameworks (e.g., Spark, Hadoop, or similar)
- Familiarity with cloud-based data or analytics platforms
- Experience deploying or operationalizing machine learning models
- Knowledge of data visualization tools (e.g., Tableau, Power BI, or equivalent)
- Experience working in an enterprise or IT-driven environment
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