Role Overview

As a Member Data Scientist, you will be part of a collaborative and innovative team dedicated to transforming data into actionable insights. You will apply statistical techniques, machine learning models, and advanced data analytics to solve complex business challenges, optimize processes, and drive decision-making.


Key Responsibilities

Data Analysis & Modeling:

  • Analyze large and complex datasets to extract meaningful patterns, trends, and insights.
  • Develop predictive and prescriptive models to solve real-world problems.

Machine Learning & AI Development:

  • Build, train, and deploy machine learning models to support business objectives.
  • Evaluate and refine models for performance and scalability.

Proficiency in Core Models:

  • Regression models (linear, logistic, ridge, lasso).
  • Classification models (decision trees, random forests, support vector machines).
  • Ensemble methods (XGBoost, LightGBM, AdaBoost).
  • Clustering models (K-means, DBSCAN, hierarchical clustering).
  • Time-series models (ARIMA, SARIMA, Prophet).
  • Neural networks (CNNs, RNNs, LSTMs, Transformers).
  • NLP models (BERT, GPT-based models, word2vec, TF-IDF).
  • Recommendation systems (collaborative filtering, content-based filtering, matrix factorization).

Data Visualization:

  • Create clear, effective visualizations to communicate insights to technical and non-technical stakeholders.
  • Develop dashboards and reports using tools like Tableau, Power BI, or similar platforms.

Collaboration & Communication:

  • Work closely with cross-functional teams, including data engineers, product managers, and business analysts, to understand requirements and deliver solutions.
  • Present findings and recommendations to stakeholders at various levels of the organization.

Research & Innovation:

  • Stay up-to-date with the latest advancements in data science and incorporate best practices into projects.
  • Explore and prototype new technologies or methodologies to enhance analytical capabilities.


Required Qualifications

  • Bachelor’s/Master’s degree in Computer Science, Statistics, Data Science, Mathematics, or a related field.
  • 3+ years of experience in data science, analytics, or a related field.
  • Proficiency in Python, R, or similar programming languages.
  • Experience with machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
  • Strong SQL skills and familiarity with database systems.
  • Expertise in data visualization tools (e.g., Matplotlib, Seaborn, Power BI, Tableau).
  • Solid understanding of statistical techniques and hypothesis testing.


Preferred Skills

  • Experience with cloud platforms like AWS, Azure, or Google Cloud.
  • Familiarity with big data tools such as Spark, Hadoop, or Kafka.
  • Exposure to advanced techniques such as deep learning, transfer learning, and reinforcement learning.
  • Experience with CI/CD pipelines and version control (e.g., Git).
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