Data Scientist - Machine Learning

Description :

Key Responsibilities :

Data Analysis & Exploration :

- Collect, clean, and analyze large datasets to identify patterns, trends, and insights.

- Perform exploratory data analysis (EDA) using statistical techniques and data visualization tools.

- Work with business stakeholders to understand data requirements and objectives.

Machine Learning & Modeling :

- Build, train, and optimize machine learning models for prediction, classification, clustering, and recommendation systems.

- Develop advanced statistical models, forecasting algorithms, and optimization solutions.

- Evaluate model performance using appropriate metrics and tune models for accuracy and efficiency.

Data Engineering Support :

- Collaborate with data engineers to design and maintain robust data pipelines.

- Ensure data quality, integrity, and availability for analytics and model lifecycle management.

- Support ETL processes and contribute to data architecture discussions.

Experimentation & Insights :

- Design and conduct A/B tests, statistical experiments, and hypothesis testing.

- Present insights, key findings, and recommendations to leadership and cross-functional teams.

- Develop dashboards and reporting tools for data monitoring and business KPIs.

Deployment & Automation :

- Work with engineering teams to deploy machine learning models into production environments.

- Monitor model performance, retrain models, and maintain version control.

- Automate model workflows, feature pipelines, and data preprocessing procedures.

Business Partnership & Strategy :

- Translate business problems into data science solutions aligned with organizational goals.

- Advise on data strategy, model impacts, and opportunities for optimization.

- Support decision-making for product features, customer insights, risk assessment, and performance

improvements.

Requirements :

Education & Experience :

- Bachelors or Masters degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.

- 2- 6 years of experience in data science or machine learning roles.

Technical Skills :

- Strong proficiency in Python or R for data analysis and model building.

- Expertise in machine learning libraries (Scikit-Learn, TensorFlow, Keras, PyTorch).

- Proficiency in SQL for data extraction and manipulation.

- Experience with data visualization tools (Tableau, Power BI, Matplotlib, Seaborn).

- Strong understanding of statistics, probability, and linear algebra.

- Familiarity with big data technologies (Hadoop, Spark) is a plus.

- Experience with cloud platforms (AWS, GCP, Azure) is preferred.

Soft Skills :

- Strong analytical and problem-solving skills with high attention to detail.

- Excellent communication and storytelling skills with the ability to explain data concepts to non-technical teams.

- Ability to work independently and collaboratively in cross-functional teams.

- Strong organizational skills and ability to manage multiple projects simultaneously.

Preferred Skills (Nice to Have) :

- Experience in NLP, computer vision, reinforcement learning, or deep learning.

- Familiarity with MLOps practices and model deployment frameworks (MLflow, Kubeflow).

- Experience in building recommendation systems, predictive analytics solutions, or customer segmentation

models.

- Knowledge of statistical tools like SAS, SPSS, or STATA