Responsibilities

Leverage data science and machine learning technology to build algorithms, statistical models and analytical solutionsUse predictive modeling to increase and optimize customer experiences, revenue generation, data insights, and other business outcomesBuild ETL pipelines in PySpark/Python that process transaction and account level data and standardize data fields across various data sourcesOrganize and manage multiple data science projects with diverse cross-functional stakeholdersWork alongside global counterparts to solve data-intensive problems using standard analytical frameworks and tools.Design & implement interactive dashboards and reports. Build visualizations of data model performance and results.Actively engage, network, collaborate with internal teams to deliver data driven solutions.Provide technical leadership in a team that generates business insights based on applied analytics. Identify actionable recommendations.  Communicate the findings to business seniors.

Pre-Requisites for candidates

10+ years of work experience with a Bachelor’s Degree or 8+ years of work experience with an Advanced degree (e.g. MTech, MSc, MBA) or 7+ years of work experience with a PhD degree(Preferred) Master’s degree in Statistics, Operations Research, Applied Mathematics, Economics, Data Science, Business Analytics, Computer Science, Marketing Research.8+ years of experience in data-based decision-making, quantitative analysis, & experience applying data science to solve problems such as new customer acquisition, attrition management and product mix models   Expertise in the following activities: Large scale data mining, data cleansing, diagnostics, preparation for Modeling. Predictive modeling and machine learning. Multivariate techniques & predictive modeling – cluster analysis, discriminant analysis, CHAID, logistic & multiple regression analysis. Building data analytics models using Python, ML libraries, Jupyter/Anaconda. Exploring data & writing analytics algorithms in Python.Working knowledge of MS Azure Suite - Azure ML Studio, Azure Data Factory, Power BI/Power AppsExperience leading other data scientists in machine learning projectsStrong verbal, writing & presentation skillsExperienced in handling multi-national projects and team engagements  (Preferred) Application of data analytics to manufacturing industries or chemical industries

Our Commitment to Diversity and Inclusion

Ecolab is committed to fair and equal treatment of associates and applicants and furthering the principles of Equal Opportunity to Employment. Our goal is to fully utilize minority, female, and disabled individuals at all levels of the workforce. We will recruit, hire, promote, transfer and provide opportunities for advancement based on individual qualifications and job performance. In all matters affecting employment, compensation, benefits, working conditions, and opportunities for advancement, Ecolab will not discriminate against any associate or applicant for employment because of race, religion, color, creed, national origin, citizenship status, sex, sexual orientation, gender identity and expressions, genetic information, marital status, age, or disability.