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Intern

Intern

ADA

0 years

0 Lacs

bengaluru karnataka india

Posted:1 day ago| Platform: Foundit logo

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Skills Required

feature engineering classification model deployment statistical modeling data collection reporting

Work Mode

On-site

Job Type

Full Time

Job Description

Job Description: Data Scientist (Intern)
Position Overview: As a Data Scientist, you will be responsible for analyzing and interpreting complex datasets to provide valuable insights and solve challenging business problems. You will work closely with cross-functional teams to gather data, build predictive models, develop algorithms, and deliver data-driven solutions. This position is ideal for a fresher who possesses strong analytical skills, programming expertise, and a passion for working with data.Key Responsibilities:

Data Collection and Preprocessing:
Collect, clean, and preprocess large volumes of structured and unstructured data from various sources.
Conduct data quality assessments and implement data cleaning techniques to ensure accuracy and reliability.
Exploratory Data Analysis (EDA):
Perform exploratory data analysis to understand the characteristics of the data and identify patterns, trends, and outliers.
Utilize statistical techniques and visualizations to gain insights from the data.
Statistical Modeling and Machine Learning:
Develop predictive models and algorithms using statistical techniques and machine learning algorithms.
Apply regression analysis, classification, clustering, time series analysis, and other relevant methods to solve business problems.
Evaluate model performance, fine-tune parameters, and optimize models for better accuracy.
Feature Engineering:
Identify and engineer relevant features from raw data to enhance model performance.
Conduct feature selection techniques to improve model interpretability and efficiency.
Model Deployment and Evaluation:
Collaborate with software engineers to deploy models into production systems.
Monitor model performance, diagnose issues, and implement improvements as needed.
Data Visualization and Reporting:
Communicate findings and insights effectively through clear and concise data visualizations, reports, and presentations.
Present complex data-driven concepts to non-technical stakeholders in a way that is easy to understand.
Continuous Learning and Research:
Stay up-to-date with the latest advancements in data science, machine learning, and related fields.
Conduct research and experimentation to explore new methodologies and approaches.

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