All fields marked * are required
Role Overview
We are looking for a Data Scientist to analyze large datasets, build predictive models, and generate actionable insights that drive business decisions. The ideal candidate should have strong analytical skills, a solid understanding of statistical techniques, and hands-on experience in machine learning.
Key Responsibilities
Analyze structured and unstructured data to extract meaningful insights.
Build, validate, and deploy machine learning models.
Perform data cleaning, preprocessing, and feature engineering.
Develop predictive and statistical models to solve business problems.
Work closely with cross-functional teams (product, engineering, business).
Create dashboards, reports, and visualizations for stakeholders.
Monitor model performance and improve accuracy over time.
Stay updated with the latest trends in data science and AI.
Required Skills & Qualifications
Bachelor’s/Master’s degree in Computer Science, Statistics, Mathematics, or related field.
2–6 years of experience in data science or analytics roles.
Strong programming skills in Python or R.
Hands-on experience with libraries such as Pandas, NumPy, Scikit-learn.
Knowledge of machine learning algorithms (regression, classification, clustering).
Strong understanding of statistics and probability.
Experience with SQL and working with large datasets.
Familiarity with data visualization tools like Tableau, Power BI, or Matplotlib/Seaborn.
Good to Have
Experience with Deep Learning / NLP
Exposure to Big Data tools (Spark, Hadoop)
Experience with cloud platforms (AWS, GCP, Azure)
Knowledge of MLOps and model deployment
Experience with A/B testing and experimentation frameworks
Key Competencies
Strong analytical and problem-solving mindset
Ability to translate data into business insights
Good communication and stakeholder management skills
Attention to detail and data accuracy
Required
All fields marked * are required
Role Overview
We are looking for a Data Scientist to analyze large datasets, build predictive models, and generate actionable insights that drive business decisions. The ideal candidate should have strong analytical skills, a solid understanding of statistical techniques, and hands-on experience in machine learning.
Key Responsibilities
Analyze structured and unstructured data to extract meaningful insights.
Build, validate, and deploy machine learning models.
Perform data cleaning, preprocessing, and feature engineering.
Develop predictive and statistical models to solve business problems.
Work closely with cross-functional teams (product, engineering, business).
Create dashboards, reports, and visualizations for stakeholders.
Monitor model performance and improve accuracy over time.
Stay updated with the latest trends in data science and AI.
Required Skills & Qualifications
Bachelor’s/Master’s degree in Computer Science, Statistics, Mathematics, or related field.
2–6 years of experience in data science or analytics roles.
Strong programming skills in Python or R.
Hands-on experience with libraries such as Pandas, NumPy, Scikit-learn.
Knowledge of machine learning algorithms (regression, classification, clustering).
Strong understanding of statistics and probability.
Experience with SQL and working with large datasets.
Familiarity with data visualization tools like Tableau, Power BI, or Matplotlib/Seaborn.
Good to Have
Experience with Deep Learning / NLP
Exposure to Big Data tools (Spark, Hadoop)
Experience with cloud platforms (AWS, GCP, Azure)
Knowledge of MLOps and model deployment
Experience with A/B testing and experimentation frameworks
Key Competencies
Strong analytical and problem-solving mindset
Ability to translate data into business insights
Good communication and stakeholder management skills
Attention to detail and data accuracy
Required