Data Scientist

Job Summary:

The ideal candidate will have a strong background in data analysis, machine learning, and statistical modeling , along with the ability to derive actionable insights from complex data sets.

Responsibilities

• Data Collection and Preprocessing:

• Acquire, clean, and preprocess data from various sources to ensure data quality and reliability.

• Work with big data technologies and tools for efficient data processing.

• Exploratory Data Analysis (EDA):

• Conduct exploratory data analysis to understand data patterns, trends, and anomalies.

• Identify relevant variables and features for further analysis.

• Statistical Modeling and Machine Learning:

• Develop and implement statistical models and machine learning algorithms to solve business problems.

• Perform predictive modeling , classification, clustering, and regression analysis as needed.

• Evaluate model performance and make improvements using techniques like cross-validation and hyperparameter tuning.

• Collaboration and Communication:

• Collaborate with cross-functional teams, including data engineers, business analysts, and software developers.

• Communicate technical concepts and results to non-technical stakeholders in a clear and understandable manner.

• Provide guidance and support to team members on data-related tasks and projects.

Qualifications

• Bachelor's or Master's degree in Data Science , Computer Science, Statistics, or a related field.

• Proven experience in data analysis, machine learning, and statistical modeling .

• Proficiency in programming languages such as Python, R, or SQL.

• Familiarity with GenAI and implementing LLM

• Familiarity with machine learning libraries/frameworks (e.g., TensorFlow, scikit-learn, PyTorch ).

• Experience with big data platforms (e.g., Hadoop, Spark) and cloud services (e.g., AWS, Azure) is a plus.

• Strong analytical and problem-solving skills with attention to detail.

• Excellent communication and collaboration abilities.

• Ability to work independently and manage multiple projects simultaneously.