Data Scientist

Role & responsibilities

Data Analysis and Modeling:

• Design and implement models to analyze large datasets for problem-solving and

prediction.

• Apply advanced machine learning algorithms and statistical methods on varied

data sets.

• Develop production-scale solutions and transform statistical/machine learning

models.

Collaboration and Communication:

• Work with product engineering and customer support to identify problems.

Collaborate with analytics team members on data analysis and machine

learning techniques.

• Present findings to product management and development personnel.

Autonomous Initiatives:

• Lead data science initiatives using statistical, machine learning, and analytics

techniques to uncover business value.

• Design research methods for strategic issues like predicting educational

outcomes.

Data Integrity and Monitoring:

• Ensure data integrity and monitor data quality throughout the lifecycle.

Preferred candidate profile

Key Skills and Qualifications:

Programming and Technical Skills:

• Proficiency in SQL tool ( Redshift, SNOWFLAKE, Mongo), Python (pandas, scikit

learn), R, and Spark. Spypark, Machine Learning Algorithms ( NLP & LLM) ,

Django,

• Knowledge of additional programming languages like Scala, Java, or C++ is

advantageous.

Statistical and Mathematical Skills:

• Proficiency in data mining, preprocessing, and data wrangling.
• Experience with data visualization tools like matplotlib, ggplot, d3.js, and

Tableau.

Soft Skills and Experience:

• Excellent communication skills for both technical and non-technical audiences.
• Strong problem-solving aptitude and analytical mind.
• Proven experience as a Data Analyst or Data Scientist.
• Strong software engineering background and hands-on experience with data

science tools.

Educational Background:

• A degree in Computer Science, Engineering, or a relevant field is preferred.