Principal Data Scientist

Precisely is the leader in data integrity. We empower businesses to make more confident decisions based on trusted data through a unique combination of software, data enrichment products and strategic services. What does this mean to you? For starters, it means joining a company focused on delivering outstanding innovation and support that helps customers increase revenue, lower costs and reduce risk. In fact, Precisely powers better decisions for more than 12,000 global organizations, including 99 of the Fortune 100. Precisely's 2500 employees are unified by four company core values that are central to who we are and how we operate: Openness, Determination, Individuality, and Collaboration. We are committed to career development for our employees and offer opportunities for growth, learning and building community. With a "work from anywhere" culture, we celebrate diversity in a distributed environment with a presence in 30 countries as well as 20 offices in over 5 continents. Learn more about why it's an exciting time to join Precisely In this role, you will be responsible for designing, building, and deploying machine learning models and algorithms that drive business growth and help solve complex business problems. You will work closely with data scientists, software engineers, and product managers to develop and deploy data-driven solutions that deliver business value. **You Will**: - As a Principal Engineer - Machine Learning you will be responsible for utilizing your analytical, statistical and programming skills to collect, analyze and interpret large data sets. This information can be used to develop data-driven solutions to solve difficult business challenges and analyze trends to make better decisions. **You Have**: - 8-12 years of experience manipulating data sets and building statistical models, has a degree in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the open source Machine learning tools - Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets. - Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. - Strong understanding of linguistic concepts like Part of Speech, Name Entity Recognition, Dependency Parsing, Parsing, Shallow Parsing and so on. - Excellent written and verbal communication skills for coordinating across teams. - A drive to learn and master new technologies and techniques. - Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc. - Experience in designing machine learning systems and self-running artificial intelligence AI software to automate predictive models. - Experience querying databases and using statistical computer languages: R, Python, SQL, etc. - Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. - Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, PySpark, MySQL, etc. **PREFERRED REQUIREMENTS**: - Experience visualizing/presenting data for stakeholders using: Qlik, D3, ggplot, etc. - Experience in OpenCV, Keras/PyTorch/Tensorflow. - Experience with cloud-native development (AWS, Azure, GCP etc.) - Experience in Data-Integrity domain - geo-spatial, Data quality, Enrich etc is a Big plus. LI-SA1