Pricing Analytics team is responsible for setting & auditing millions of prices every day and relies on analytics based systems including machine learning models to have accurate prices.
Scale of this operation and the pricing risk involved requires us to evolve our analytics platform in the pricing quality team and we are looking for candidates who can assist in making key data-
related decisions by extracting, analyzing, manipulating, tracking, internally managing and reporting data, as well as Key Performance Indicators (KPIs) by working with cross-
functional teams. The analyst will have demonstrated analytical thinking, problem solving, and statistical / programming skills along with strong business aptitude.
Roles & Responsibilities :
Critically evaluate information gathered from multiple sources, decompose high-level information into details, abstract up from low-
level information to a general understanding, and build robust processes to enable the highest quality of pricing inputs
Handle ambiguous and large data sets and execute high priority (i.e. cross functional, high impact) projects to improve operations performance / drive Quality metrics with the help of Operations Analytics managers
Provide design / structural inputs and occasionally mentor MIS Analysts to develop highly available dashboards for tracking Project Metrics.
You will need to identify new pattern of errors and make recommendations for new controls and improved price monitoring Design.
High level of mathematical aptitude and strong problem-solving skills is a must
Work closely with your peers, operations managers to understand their requirement and translate in to actionable metrics
Required to have a logical, analytical and investigative mind, together with creative abilities to conduct in-depth and detail oriented based business analysis to provide insights / root causes for business performance, new opportunity identification and business case preparation driving quality pricing inputs.
Use data heavily to recognize patterns / trends to drive a team of Quality Analysts to spot pricing errors, size up problems through various audits, convert problem statements into process improvement activities & achieve closure
Work closely with the Technical team in terms of giving actionable inputs to build intelligent Analytical / Machine Learning models that will drive the quality metrics
Responsible for auditing operations teams & system outputs, leading and implementing process / system improvements, and identifying emerging process performance trends
Use of statistical analysis to segment Pricing errors and put in place robust Quality Control checks
Understand the requirements of Operations managers / others and map them with the data sources / data warehouse - your ability to execute analytical projects by working on huge data sets will be required
2 years of prior experience working in ecommerce / retail / services / financial services business is required
At least 18 months of experience working in Analytics / Machine Learning / Statistical Modeling / Business Intelligence environment
Has problem solving skills and attention to details, proficient in MS Excel and analytical scripting languages python / R
Ability to apply analytical, statistical and quantitative problem solving skills is required along with proficiency in use of analytical packages and must have experience in building ML solutions.
Has working knowledge of supervised learning algorithms; Decision trees, ensemble models (Random Forest, bagging and boosting), text analytics (parsing, pre-
processing, topic modeling, text classification) and has the ability to build prototypes with quick turnaround using R (dplyr, mlr etc.
or python (pandas, numpy, scipy, scikit learn) and basic knowledge of regression and forecasting techniques.
Detail-oriented and an aptitude to solve unstructured problems. The role will require the ability to extract data from various sources (basic knowledge of SQL and tableau is required) & to design / construct / execute complex analyses that help solve the business problem
Ability to be adaptable and flexible in responding to deadlines and workflow fluctuations
Excellent written and verbal communication skills with the ability to articulate statistical and analytical concepts to non-tech stakeholders.
Certifications in any quantitative discipline such as Statistics, Mathematics, Quantitative Finance or Operational Research is an added advantage
MS in statistics / MBA is a plus