Data Scientist

Job Summary:

We are seeking a highly skilled and motivated Data Scientist with a strong background in Artificial Intelligence (AI) and Machine Learning (ML) to join our growing analytics team. You will be responsible for designing, developing, and deploying data-driven models and AI solutions that solve real-world business problems and drive strategic decision-making.

Key Responsibilities:

Develop and implement advanced machine learning models, AI algorithms, and statistical models to analyze large, complex datasets.

Apply data mining techniques and perform predictive and prescriptive analytics.

Design and conduct experiments (e.g., A/B testing, simulation models) to evaluate model performance and business impact.

Collaborate with cross-functional teams including engineering, product, and business stakeholders to identify opportunities for leveraging data to drive innovation.

Build and maintain end-to-end ML pipelines for model training, validation, deployment, and monitoring.

Interpret and communicate findings and insights to both technical and non-technical audiences.

Stay current with the latest research and trends in AI/ML and integrate relevant advancements into ongoing projects.

Required Skills & Qualifications:

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.

3+ years of experience working in a Data Science or Machine Learning role.

Proficiency in Python and common libraries (e.g., scikit-learn, pandas, NumPy, TensorFlow, PyTorch).

Strong background in machine learning, deep learning, natural language processing, or computer vision.

Experience with model evaluation techniques (ROC, F1-score, confusion matrix, etc.).

Proficient in querying and working with large datasets using SQL or NoSQL databases.

Experience with data visualization tools (e.g., matplotlib, seaborn, Power BI, or Tableau).

Strong communication and storytelling skills with the ability to explain complex concepts.

Preferred Qualifications:

Ph.D. in a quantitative field (optional but advantageous).

Experience deploying models into production using Docker, Kubernetes, MLflow, or MLOps tools.

Familiarity with cloud platforms (AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark).

Domain experience in [insert domain: finance, healthcare, retail, etc.].

Why Join Us:

Work on cutting-edge AI/ML initiatives with real business impact.

Join a team that values innovation, experimentation, and continuous learning.

Competitive compensation and benefits package.

Opportunity to work with a diverse and talented team.