Data Scientist

Hunters International Sdn Bhd; Kuala Lumpur; On-site; MYR 60,000 - 80,000; Full time

Job summary

A technology-focused company in Kuala Lumpur is seeking a Data Scientist to identify and extract valuable data, utilize machine learning algorithms for analysis, and ensure data integrity. The ideal candidate will have a degree in a related field, at least one year of relevant experience, and strong programming skills in R and Python. This role involves collaboration with cross-functional teams to align data initiatives with business objectives.

Qualifications

• A degree in Computer Science, Engineering, or a related field.
• Min 1 year experience in Data Scientist role.
• Proficiency in R and Python for statistical analysis and machine learning.
• Strong foundation in applied statistics.
• Familiarity with various machine learning algorithms.
• Ability to preprocess and clean datasets.
• Hands-on experience with data science tools and libraries.
• Ability to think critically about data in a business context.

Responsibilities

• Identify and extract valuable data from various sources.
• Utilize machine learning algorithms to choose relevant features.
• Clean and format both structured and unstructured data.
• Implement processes to ensure data quality.
• Employ statistical methods to analyze large datasets.
• Design and develop algorithms that predict outcomes.
• Suggest data-driven strategies to address business problems.
• Work closely with cross-functional teams.

Skills

Data Mining

Machine Learning

Programming in R

Programming in Python

SQL proficiency

Statistics

Data Wrangling

Analytical Thinking

Experience with big data technologies

Cloud platforms (AWS, Azure, Google Cloud)

Education

Degree in Computer Science, Engineering, or related field

Tools

scikit-learn

TensorFlow

Hadoop

Spark

Job description

Responsibilities

• Data Mining: Identify and extract valuable data from various sources such as databases, APIs, and web scraping.
• Feature Selection and Classification: Utilize machine learning algorithms to choose the most relevant features from the dataset, develop classifiers, and refine them for better accuracy.
• Data Preprocessing: Clean and format both structured (like SQL databases) and unstructured data (like text or images) to prepare it for analysis.
• Data Integrity: Implement processes to ensure data quality by validating and cleansing datasets to eliminate inconsistencies and errors.
• Pattern Analysis: Employ statistical methods and machine learning techniques to analyze large datasets, uncover trends, and derive actionable insights.
• Predictive Modeling: Design and develop algorithms that predict outcomes based on historical data, helping to inform strategic business decisions.
• Solution Proposals: Suggest data-driven strategies to address specific business problems, leveraging analytical insights to improve decision-making.
• Collaboration: Work closely with cross-functional teams, including Business and IT, to align data initiatives with organizational goals and ensure technical feasibility.

Requirements

• Educational Background: A degree in Computer Science, Engineering, or a related field.
• Proven Experience: Demonstrated Min 1 year experience in Data Scientist role, showcasing the ability to apply these skills in real-world scenarios.
• Programming Skills: Proficiency in languages like R and Python for statistical analysis and machine learning, alongside SQL for querying databases.
• Statistics: Strong foundation in applied statistics, understanding key concepts such as statistical tests, probability distributions, regression analysis, and maximum likelihood estimation.
• Machine Learning: Familiarity with various machine learning algorithms, and enabling these selection of appropriate models for specific tasks.
• Data Wrangling: Ability to preprocess and clean datasets, addressing issues like missing values, inconsistencies, and outliers to ensure data quality.
• Hands-on Experience with Data Science Tools: Practical experience using various data science tools and libraries, such as scikit-learn, TensorFlow, or similar platforms, to implement machine learning and analysis tasks.
• Analytical Mind and Business Sense: Ability to think critically about data in a business context, linking insights to strategic objectives and operational decisions.
• Experience with big data technologies (e.g., Hadoop, Spark) is a plus.
• Familiarity with cloud platforms like AWS, Azure, or Google Cloud.