Senior Data Scientist (Hybrid)

We are seeking a highly skilled experienced and motivated Senior Data Scientist to join our team. 

As a Data Scientist, you will be responsible for the full data cleaning and analysis pipeline, employing your strong analytical and problem-solving skills to derive actionable insights. This role requires a fair amount of data engineering expertise, enabling you to transform raw data into usable formats and optimize data workflows.

Responsibilities:

1. Data Cleaning and Preprocessing: Perform thorough data cleaning, validation, and preprocessing to ensure the accuracy and reliability of the data used in analysis. Identify and handle missing data, outliers, and inconsistencies, maintaining data integrity throughout the pipeline.
2. Exploratory Data Analysis (EDA): Conduct comprehensive EDA to uncover patterns, trends, and correlations within the data. Apply statistical techniques and data visualization to communicate findings effectively.
3. Advanced Statistical Analysis: Perform advanced statistical analysis, including statistical testing and measuring statistical feature associations. Apply a wide range of statistical techniques to identify significant relationships, assess the impact of variables, and measure the strength of associations.
4. Modeling and Algorithm Development: Design and implement machine learning algorithms and statistical models to solve business problems and extract valuable insights from complex datasets. Collaborate with cross-functional teams to develop predictive models, optimize algorithms, and improve existing methodologies.
5. Building Forecasting Models: Utilize machine learning and deep learning techniques to develop accurate and reliable forecasting models. Apply time series analysis, regression, and other forecasting methodologies to predict future trends, demand, and outcomes.
6. Data Engineering: Develop and maintain scalable data pipelines, integrating and transforming data from various sources. Utilize data engineering techniques to streamline data acquisition, storage, and processing, ensuring efficient data flow across the organization.
7. Writing Optimized SQL Queries: Write efficient and optimized SQL queries for data analysis and retrieval. Utilize advanced SQL techniques to extract and manipulate data from relational databases, ensuring optimal performance and scalability.
8. Building Custom Live/Near Live Dashboards: Design and develop custom live/near live dashboards with complex functionality that integrate various data sources. Utilize business intelligence tools such as Tableau or Power BI to create interactive and visually appealing dashboards that enable real-time monitoring and analysis of key performance indicators.
9. Writing High-Quality and Organized Code: Ensure that code written for data cleaning, analysis, modeling, and engineering is of high quality, well-documented, and follows best practices. Write clean, efficient, and modular code that is easy to understand and maintain.
10. Communication and Visualization: Clearly communicate complex findings, methodologies, and insights to both technical and non-technical stakeholders. Visualize data and present results through compelling visualizations, dashboards, and reports.