Position:
Data Science Engineer
No of Positions:
3
Qualification:
Any Graduate / Post Graduate
Experience:
Fresher / Experience
Location:
Chennai,Bangolore
Country:
India
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Data Science Engineer
Primary Skills:
Job Roles and Responsibilities:
- Collecting, cleaning, and preprocessing data from various sources such as databases, APIs, and files. Integrating and merging data from disparate sources to create a unified dataset suitable for analysis.
- Exploring and visualizing data using statistical and graphical techniques to gain insights and identify patterns. Creating informative visualizations, such as charts, graphs, and dashboards, to communicate findings to stakeholders.
- Applying statistical techniques and machine learning algorithms to analyze data and extract meaningful patterns and trends.
- Engineering new features from raw data or existing features to enhance model performance. Selecting relevant features and reducing dimensionality to improve model interpretability and efficiency.
- Implementing machine learning algorithms such as regression, classification, clustering, and ensemble methods.
- Deploying machine learning models into production environments, either as APIs, batch processes, or embedded within applications.
- Monitoring model performance in production and detecting drift or degradation over time.
- Ensuring compliance with data governance policies, regulations, and ethical guidelines.
- Collaborating with cross-functional teams, including data engineers, software developers, and business stakeholders, to define project goals and requirements.
Required Experience, Skills, Knowledge:
- Experience in analyzing large datasets and building machine learning models to solve real-world problems. Experience with data manipulation, preprocessing, and feature engineering techniques. Proficiency in programming languages commonly used in data science such as Python or R. Experience with data visualization tools and techniques for communicating insights effectively.
- Understanding of probability theory, linear algebra, and calculus as they relate to machine learning algorithms.
- Proficiency in statistical analysis and hypothesis testing to derive actionable insights from data. Strong knowledge of machine learning algorithms and techniques for regression, classification, clustering, and anomaly detection.
- Knowledge of data engineering concepts and tools for data acquisition, storage, and processing. Familiarity with big data technologies such as Hadoop, Spark, or Apache Kafka for handling large-scale datasets.
- Knowledge of domain-specific techniques and algorithms relevant to the industry or problem domain.
Soft Skills:
- Team player and individual contributor
- Self-starter and highly motivated
- Excellent communication skills