Brief Description of position:

About Innover (innoverdigital.com): We are an Atlanta based digital transformation company.  We are dynamic, fast growing, and fun! If you are looking to work for a firm where your impact is  visibly not only to you but also in firm’s growth, join us! 

As a Digital Company, Innover focuses on 5 Service Areas – Business Consulting Services, Digital Experience, Data Engineering, Advanced Analytics and Product/Software Engineering. Apart  from these studios, Innover Labs focuses on investing in latest and emerging technologies like  Blockchain, Internet of Things and AR/VR and their application to practical business problems. 

Job Summary: 

We are actively seeking a skilled motivated Data Scientist professionals who will support and own  multiple projects globally that drive business growth while still balancing compliance risk and  partner friction. The role will cover areas such as (not limited to) Sanctions screening; Partner and  user compliance; Customer due diligence; Transaction monitoring; Metrics development and  monitoring; and Model and Strategy development - to help balance partner friction and compliance  risk. 

We will rely on you to build data products to extract valuable business insights. In this role, you  should be highly analytical with a knack for analysis, math and statistics. Critical thinking and  problem-solving skills are essential for interpreting data. We also want to see a passion for  machine-learning and research. Your goal will be to help our company analyze trends to make  better decisions. 

Key Responsibilities include: 

• Develop and manage user risk rating models that meet applicable regulatory requirements  and are aligned with standard methodologies and practices. 
• Interpret large amounts of complex data to formulate problem statements, concise  conclusions regarding underlying risk dynamics, trends and opportunities Identify key risk indicators and metrics while developing and monitoring key parameters, enhance  reporting, and identify new areas of analytic focus to better understand operational risk. 
• Coordinates research and analytic activities utilizing various data points (unstructured and  structured) and employ programming to clean, massage, and organize the data.
• Experiments against data points, provide information based on experiment results and  provide previously undiscovered solutions to command data challenges. 
• Build predictive models and machine-learning algorithms.
• Combine models through ensemble modeling.
• Leads all data experiments tasked by the Data Science Team.
• Develops methodology and processes for prioritization and scheduling of projects.
• Analyzes problems and determines root causes. 
• Devise and utilize algorithms and models to mine big data stores, perform data and error  analysis to improve models, and clean and validate data for uniformity and accuracy.
• Implement analytical models into production by collaborating with software developers  and machine learning engineers.
• Analyze data for trends and patterns, and Interpret data with a clear objective in mind.
• Communicate analytic solutions to stakeholders and implement improvements as needed to  operational systems. 
• Present information using data visualization techniques. 
• Extensive data analytics and SQL query writing Predictive modeling / Machine learning  algorithms - using random Forest / Decision tree / Logistic regression. 

Requirements: 

• Proven hands-on experience in a data-focused role such as product analytics, business  analytics, business operations, or data science Education in Engineering, Computer Science,  Math, Economics, Statistics or equivalent experience. 
• Write efficient and complex code in SQL. 
• Proven track record to handle large datasets, explore and apply raw data feeds.
• Excellent data visualization skills. 
• Love of data - you just go get the data you need and turn it into an insightful story.
• Experience with Excel, PowerPoint, Tableau, SQL, and programming languages (i.e.,  Java/Python, SAS). 
• Advanced analytical knowledge of data.
• Understanding of machine-learning and operations research. 
• Conducting big data analysis.
• Data conditioning.
• Programming advanced computing.
• Developing algorithms.
• Developing software and data models.
• Executing predictive analytics.
• Comfort working in a dynamic, research-oriented group with several ongoing concurrent  projects.
• Analytical mind and business acumen.
• Strong math skills (e.g. statistics, algebra).
• Problem-solving aptitude.
• Excellent communication and presentation skills.