The Data Scientist will analyze large datasets, build machine-learning models, and present insights to stakeholders while collaborating in an Agile environment.
Responsibilities
- Process, cleanse, and verify the integrity, accuracy, and consistency of data used for analysis.
- Perform ad‑hoc analyses and present insights and findings in a clear and structured manner to stakeholders.
- Analyze large and complex datasets to extract insights and determine the most appropriate analytical or machine‑learning techniques.
- Select features, build, train, evaluate, and optimize machine‑learning models and classifiers.
- Apply data mining techniques using state‑of‑the‑art methods to identify patterns, trends, and anomalies.
- Use data modeling and evaluation strategies to predict future trends and support proactive decision‑making.
- Develop and enhance data collection procedures to improve the relevance and quality of data used in analytical systems.
- Enrich internal datasets using third‑party data sources where required.
- Design and develop dashboards and reports to effectively communicate insights and KPIs to business stakeholders.
- Collaborate with business partners to understand requirements, translate them into data‑driven solutions, and communicate recommendations effectively.
- Work in an Agile environment for applied research and analytics delivery.
- Read and adhere to the Underwriters Laboratories Code of Conduct and follow all physical and digital security practices.
- Perform other duties as directed.
- Bachelor’s degree in Data Science, Data Analytics, Computer Science, or a related field of science.
- Minimum 4+ years of hands‑on experience in data science, data analytics, or a related analytical role.
- Strong problem‑solving skills with an emphasis on analytical and business impact.
- Strong proficiency in SQL, including complex joins, aggregations, subqueries, and performance optimization.
- Experience querying databases and working with large datasets.
- Strong Python programming skills for data analysis, modeling, and statistical computation.
- Experience using statistical and data manipulation libraries such as Pandas and NumPy.
- Hands‑on experience with a variety of machine‑learning techniques, including understanding their real‑world advantages and limitations.
- Detailed knowledge of machine‑learning evaluation metrics and best practices.
- Experience with end‑to‑end machine‑learning development, from data preparation through model evaluation.
- Experience with data visualization tools, preferably Power BI, including calculated columns and business logic (DAX).
- Experience validating analytical outputs and dashboard metrics against source data.
- Strong analytical, communication, and presentation skills.
- Demonstrated effective interpersonal, influencing, collaboration, and listening skills.
Top Skills
Numpy
Pandas
Power BI
Python
SQL
Bro4u.com Bengaluru, Karnataka, IND Office
4 1st Cross Road, Bengaluru, Karnataka, India, 560010
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