Data Scientist

Job Summary:

We are looking for a highly skilled and experienced Data Scientist to join our growing analytics team. As a Data Scientist, you will be responsible for extracting insights from large, complex datasets, building predictive and prescriptive models, and helping to drive data-driven decisions across the organization. You will work closely with cross-functional teams to design experiments, prototype solutions, and implement algorithms that have a tangible impact on the business.

Key Responsibilities:

Data Exploration & Analysis:

• Understand business objectives and translate them into data science problems.
• Perform exploratory data analysis using statistical techniques and visualization tools.
• Analyze structured and unstructured data from multiple sources (databases, APIs, flat files, etc.).

Model Development:

• Build and validate machine learning and statistical models (classification, regression, clustering, NLP, time-series, etc.).
• Optimize model performance using feature engineering, hyperparameter tuning, and model selection techniques.
• Use ML Ops tools for model deployment and monitoring in production environments.

Business & Stakeholder Collaboration:

• Collaborate with business stakeholders, analysts, engineers, and product teams to gather requirements and present findings.
• Translate complex analytical concepts into business-friendly language.
• Support experimentation and A/B testing frameworks.

Data Engineering Support:

• Work with data engineers to define data pipelines and ensure high data quality.
• Write efficient, reusable, and modular code in Python, SQL, or Spark.
• Assist in creating and maintaining data lakes, feature stores, or model registries.

Documentation & Reporting:

• Maintain detailed documentation of methodologies, models, assumptions, and results.
• Create dashboards and reports to communicate key insights to stakeholders.

Required Skills & Qualifications:

• Bachelor’s/Master’s/Ph.D. in Computer Science, Statistics, Mathematics, Engineering, or related field.
• 2-3 years of hands-on experience in a data science or machine learning role.
• Proficiency in Python or R, and SQL. Experience with frameworks like scikit-learn, TensorFlow, PyTorch, or XGBoost.
• Strong grasp of statistical modeling, hypothesis testing, and machine learning algorithms.
• Experience with data wrangling using tools like Pandas, Spark, or Dask.
• Exposure to cloud platforms like AWS, GCP, or Azure.
• Familiarity with version control (Git), CI/CD, and containerization (Docker) is a plus.
• Excellent problem-solving and communication skills.

Preferred Qualifications:

• Experience with time-series forecasting, natural language processing, or computer vision.
• Understanding of big data platforms (Hadoop, Hive, Presto).
• Knowledge of ML Ops frameworks like MLflow, Kubeflow, or SageMaker.
• Prior experience in domains like retail, finance, healthcare, automobile, or marketing analytics.