Job Description

Description Data Analyst \xe2\x80\x93 As part of our global Data & Analytics (DnA) capability, we partner with various businesses to help define/shape their Data & Analytics Strategies and deliver outcomes. DnA team helps Koch companies unlock business value using advanced analytics (Data Analysis, Data Science, Machine Learning, Artificial Intelligence). We are a team of Data Scientists, Decision Scientists, Data Analysts, Data Engineers, Consultants and technologists that support business in their Digital Transformation journeys and help them achieve their Strategic imperatives. We are looking for an Analyst to join our Model Monitoring team. This role requires individuals who excel at executing an analytics vision, with a focus on efficiency and sustainable value creation, using data transformation, data analysis, converting business problems into analytical problems, quickly iterating on machine learning / analytics models, and building and deploying analytical solutions in a sustainable manner to deliver value to our internal client organizations. The analyst must be highly effective at being the key collaborative point between Business Leaders, Engagement Leaders, Data Scientists, and Data & Analytics/IT teams Job Responsibilities

• • Monitor health of the ML models, identify anomalies in model performance & inform business or work with different groups to resolve the problem
  • Real time tracking of the deployed models using Statistical KPIs like R-Square, Regression Error Metrics and Recall, Precisions etc. and Business specific KPIs for Data Drift and Concept drift. Recommend the need of retraining for the models to meet change in the market trends and help the data science team in area to focus on during retraining
  • Incorporate business logic for customized Alert System and closely work with Data Science and Data Engineering team to fix the anomalies detected and implement thresholds for all the output combinations.
  • Serve as the primary contact for execution and collaboration across teams \xe2\x80\x93 Business, Engagement Leaders, Decision Science team, IT etc. to understand business framework and help them building optimized solutions. Root case analysis in case of Model drifts and narrow down to the improvement areas
  • Be part of Model Monitoring Strategies for Enterprises and build a scalable solution and work with leads for team\xe2\x80\x99s visions and roadmaps
  • Evangelize the Model Monitoring framework with Data Science teams across the organization and train them on the framework on value addition and understand their current monitoring process to build an integrated platform
  • Identify automation opportunities and implementing to ensure reduction in delivery cycles and improved efficiency.

Experience & Skills required

• • 7+ years of Analytics experience and 3+ years of relevant experience delivering results from analytics projects; including close collaboration with stakeholders from IT, business and data science team. Critical thinking, exploratory Data Analysis and Reporting would be the primary responsibilities.
  • Must have strong analytical thinking and eagerness to solve complex business problems and provide optimized solutions
  • Hands-on experience with one or more of advanced analytics tools like Python, SAS, R for building data flow pipeline and integrating with existing framework
  • Should have experience in understanding all the parameters of ML Models and its statistics. Perform root cause analysis in case of any anomalies and recommend the fixes for increasing model accuracy
  • Expertise on data extraction, cleaning and data wrangling from multiple data sources like HIVE, Oracle, Redshift, Teradata, EHANA etc. Also require experience on parsing data from api
  • Should have strong experience in tools like Databricks or AWS for maintaining the code base, Orchestrations and triggering jobs based on required cadence
  • Experience in presenting data using visualization tools like Power BI, Tableau and share insights with stakeholders. Monitoring performance KPIs of deployed ML models, validating input data quality, Statistical analysis on the model outputs vs actuals will be highly required for the position
  • Drive the team as per the roadmaps and ensure highest quality of deliverables
• What will put you ahead
  • Knowledge on Machine Learning and Data Science solutions. Statistical analysis like univariate, bivariate, correlation, Statistical modelling etc.
  • Exposure on end to end MLOps pipeline using tools like AWS Sagemaker, Databricks,C3.ai,H2O.ai or any equivalent platforms.
  • Part of Data Quality and Data Governance check. Ensuring 5 dimensions of data quality \xe2\x80\x93 Accuracy, Completeness, Reliability, Relevance, and Timeliness on the input data for ML models
  • Working with the consultant and the business stakeholders to iterate on hypotheses creation and the related workshop

Koch is proud to be an equal opportunity workplace