Data Scientist

As a Data Scientist, you will be responsible for managing end-to-end delivery of data science projects. You will develop and validate predictive models using analytical tools and collaborate with the BD team, product managers, data engineers, and other teams to deploy analytical solutions. Supporting internal teams in developing in-house products and analytical solutions will also be a key part of your role. You will work on building models for descriptive and predictive analytics, exploring various areas such as natural language understanding, conversational AI, forecasting, and automation. Additionally, you will provide expertise in data wrangling, exploratory data analysis, and feature engineering with large data sets, as well as support the development of proofs of concept to demonstrate the application of analytical capabilities in solving customer problems in collaboration with product and other development teams. Aligning the technology solution with business goals is also a crucial aspect of this role. To qualify for this position, you should hold a Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or other quantitative fields. Familiarity with Agile methodologies and software development project management is required. Excellent written and verbal communication skills are essential, with experience in presenting complex technical information to non-technical audiences. Demonstrated flexibility, creativity, and patience in adapting to new situations and changing needs are also valued qualities. In terms of skills, you should have proven abilities in translating analytics output into actionable recommendations and delivering them to key stakeholders. Experience in extracting and aggregating data from large datasets, understanding and analyzing data using statistical software (e.g., Python, R, SQL, PySpark, etc.), and proficiency in Excel, PowerPoint, and BI tools such as Tableau and PowerBI are necessary. You will be expected to assess the effectiveness and accuracy of new data sources and data gathering techniques, develop custom data models and algorithms, and use predictive modeling to optimize customer experiences, revenue generation, data insights, and other business outcomes. Creating processes and tools to monitor and analyze model performance and data accuracy, partnering with key stakeholders/clients to understand problem statements, convincing them with data, and deriving relevant insights are also key responsibilities. Developing visualizations to make complex analyses accessible to a broad audience, demonstrating leadership and stakeholder management skills, maintaining high attention to detail and quality, and being highly adaptive and comfortable working within a complex environment are additional attributes that will contribute to your success in this role.,