Description: Remote. We are seeking a talented and motivated Mid-Level Data Scientist to join our dynamic team. The ideal candidate will possess a strong foundation in data science methodologies, with a particular emphasis on machine learning, exploratory data analysis, and causal inference. You will be responsible for analyzing complex datasets, developing predictive models, and providing actionable insights to drive business decisions. Key Responsibilities:

• *Data Analysis**: Conduct exploratory data analysis (EDA) to uncover trends, patterns, and anomalies in large datasets.
• *Model Development**: Build and implement machine learning models using Python libraries such as Scikit-learn, focusing on clustering and forecasting techniques.
• *Causal Inference**: Apply causal inference methodologies to assess the impact of interventions and provide recommendations based on findings.
• *Collaboration**: Work closely with cross-functional teams, including data engineers, product managers, and business stakeholders, to understand data needs and deliver insights.
• *Documentation**: Maintain clear and organized documentation of data processes, methodologies, and findings to ensure reproducibility and knowledge sharing.
• *Code Quality**: Write clean, efficient, and well-documented code, adhering to best practices in software development.

Qualifications:

• *Education**: Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or a related field.
• *Experience**: 3-5 years of experience in data science or a related field, with a proven track record of successful project delivery.
• *Technical Skills**:
• Proficiency in Python and its data science libraries (e.g., Scikit-learn, Pandas, NumPy).
• Strong understanding of machine learning algorithms and techniques, particularly clustering and forecasting.
• Familiarity with causal inference methods and their applications in data analysis.
• *Analytical Skills**: Strong analytical and problem-solving skills, with the ability to interpret complex data and communicate findings effectively.
• *Organizational Skills**: Excellent coding practices and organizational skills, ensuring code is maintainable and scalable.
• *Communication**: Strong verbal and written communication skills, with the ability to present technical concepts to non-technical stakeholders.

Additional Information: What project or initiative will they be working on?

• Application Analytics.

Top 3 Skills Needed or Required: Preferred Qualifications:

• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau).
• Knowledge of SQL and experience with relational databases.
• Familiarity with cloud platforms (e.g., AWS, Google Cloud) and big data technologies (e.g., Hadoop, Spark).

What are the day-to-day responsibilities?

• Hired resource will be responsible for analyzing complex datasets, developing predictive models, and providing actionable insights to drive business decisions.

What is the makeup of the team?

• This will be augmented to Data science and Analytics team in Product Ops.

Required Skills : SQL Additional Skills : Data Scientist