Data Scientist - Python (3-6 yrs)

Responsibilities :

Data Exploration and Preprocessing :

- Collect, clean, and preprocess large and complex datasets from various sources.

- Perform exploratory data analysis (EDA) to understand data patterns, identify anomalies, and gain insights.

- Implement feature engineering techniques to create relevant and informative features for modeling.

Model Development and Evaluation :

- Develop and implement machine learning models (classification, regression, clustering, etc.) using appropriate algorithms and techniques.

- Evaluate model performance using relevant metrics and statistical methods.

- Fine-tune models to optimize for accuracy, performance, and generalization.

Statistical Analysis and Inference :

- Apply statistical methods to analyze data, test hypotheses, and draw meaningful inferences.

- Design and conduct experiments to validate hypotheses and evaluate the impact of different strategies.

Communication and Visualization :

- Communicate complex data insights and model findings clearly and concisely to both technical and non-technical audiences.

- Create compelling data visualizations using tools like Matplotlib, Seaborn, or Tableau to effectively convey key findings.

- Present results and recommendations to stakeholders in a clear and understandable manner.

Deployment and Monitoring :

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

- Develop and implement monitoring systems to track model performance and identify potential issues.

- Iterate on models based on real-world performance and feedback.

Collaboration and Learning :

- Work closely with product managers, engineers, and other stakeholders to understand business needs and translate them into data science problems.

- Stay up-to-date with the latest advancements in data science, machine learning, and related technologies.

- Contribute to the team's knowledge sharing and best practices.

Required Skills :

- Bachelor's or Master's degree in a quantitative field such as Computer Science, Data Science, Statistics, Mathematics, Economics, or a related discipline.

- 3-6 years of professional experience as a Data Scientist.

- Strong proficiency in Python and relevant data science libraries (i.e., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).

- Solid understanding of machine learning algorithms and their applications.

- Experience with statistical modeling and inference techniques.

- Proven ability to perform data exploration, cleaning, and preprocessing.

- Experience in feature engineering and selection.

- Strong data visualization skills using Python libraries or tools like Tableau/Power BI.

- Excellent communication and presentation skills.

- Strong problem-solving and analytical skills.

- Ability to work independently and collaboratively within a team environment.

- Experience with SQL for data querying and manipulation.

- Familiarity with version control systems (i.e. Git).

Preferred Skills :

- Experience with cloud computing platforms (i.e., AWS, Azure, GCP) and their data science services.

- Familiarity with big data technologies (i.e., Spark, Hadoop).

- Experience with deploying machine learning models in production.

- Knowledge of deep learning techniques.

- Experience with time series analysis or natural language processing (NLP).

- Contributions to open-source data science projects