Data Scientist

Pearl Technologies invests time and support into its employees to give them the space to learn and grow their skills and advance in their careers. We are an organization with an entrepreneurial mindset that welcomes and supports individual ideas and strategies. We are currently expanding and are looking for a motivated and experienced Data Scientist to join our team in India. Responsibilities Understand the business requirements and processes around advanced analytics model execution. Collect data from various structured and unstructured sources to support model development. Use data mining techniques to extract data, discover trends, and draw insights; analyze forecasting metrics. Perform initial data analysis with the goal of uncovering trends, identifying the root causes of forecast inaccuracies and developing innovative features that can create additional value. Build machine learning models with advanced analytics techniques to extend our capabilities and deliver new business value. Capture and present data-driven business insights. Establish scalable, efficient, automated processes for large-scale data analysis, model development, model validation, and model implementation. Work closely with software engineering teams to drive real-time model implementation and new feature creation. Leverage existing data sources, identify and extract data from new sources, identify opportunities for, and implement primary data collection efforts, and provide recommendations on scaling new methods more widely. Requirements University degree or equivalent in data analytics, statistics, math, or computer science, with a minimum of 5 years relevant experience. 3+ years of hands-on experience as a Snowflake Practitioner in a Data Engineering role. Must be Snowflake Certified or have experience in Snowflake. The SnowPro® Advanced: Data Scientist Certification is preferred. Excellent knowledge of Python and SQL. Experience on Azure ML Studio is Preferred. Experience with Azure and AWS Services. Experience with big data processing and the development of Python and SQL scripts for large volumes of data. Considerable experience with unit and integration testing. Excellent analytical, storytelling, and problem-solving skills. Ability to communicate analytics recommendations to both technical and non-technical team members. Strong understanding of quantitative (univariate and multivariate) analysis techniques. Experience with predictive modeling and machine learning. Strong experience with statistical analytical techniques, data mining, machine learning, and predictive models using Python, R, PySpark, Matillion or similar tools. Experience with collecting, organizing, and manipulating data using scripting languages. Ability to work with data with significant ambiguity, develop creative approaches to analytical problems, and interpret data and results from a business/industry perspective. Benefits Competitive Salary Career Growth Remote Role