Data Scientist

Payroll

• About the Role:

Data Scientist

Key Responsibilities:

• Analyze large volumes of structured and unstructured data to uncover patterns, trends, and actionable insights.
• Build and deploy

  predictive models and statistical algorithms

  for business use cases such as churn prediction, anomaly detection, predictive maintenance, time-series forecasting, etc.
• Work on

  end-to-end ML pipeline

  involving data preprocessing, feature engineering, model training, validation, and deployment.
• Develop

  dashboards, KPI reports, and visualizations

  using Power BI / SQL / Python.
• Collaborate with business stakeholders, product owners, and engineering teams to define data science use cases and translate them into scalable analytical solutions.
• Present findings and models to technical and non-technical audiences through visualizations, documents and reports.
• Work on

  telecom or high-volume data domains

  , applying ML and data science techniques to improve operational efficiency and customer outcomes.
• Optional: Work on

  Generative AI / LLM use cases

  such as chatbots, document question answering or summarization.

Technical Skills Required:

• Programming

  : Python (Pandas, NumPy, Scikit-learn), SQL

• Machine Learning

  : Regression, Classification, Clustering, Time Series Models, Random Forest, XGBoost, SVM

• Deep Learning

  (Preferred): TensorFlow / PyTorch, CNN / RNN

• NLP/Generative AI

  (Good to have): OpenAI GPT, LangChain, Transformers

• Visualization Tools

  : Power BI, Matplotlib, Seaborn

• Data Handling

  : Structured & Unstructured data, Feature Engineering

• Cloud / Big Data

  : AWS, Azure, GCP, BigQuery, etc. (Preferred)

• Tools

  : Jupyter, Git, Docker, Airflow (Good to have)

Soft Skills:

• Strong analytical and problem-solving mindset.
• Excellent communication and storytelling ability.
• Ability to work independently as well as in a collaborative environment.
• Stakeholder engagement and presentation skills
  

Educational Qualification:

• Bachelors or Master’s degree in Computer Science, Data Science, Statistics, Engineering, or related discipline
• Certifications in Data Science / Machine Learning / Azure / AWS (added advantage)