Role Proficiency:

Provide expertise on data analysis techniques using software tools. Under supervision streamline business processes.

Outcomes:

      Design and manage the reporting environment; which include data sources security and metadata.       Provide technical expertise on data storage structures data mining and data cleansing.       Support the data warehouse in identifying and revising reporting requirements.       Support initiatives for data integrity and normalization.       Assess tests and implement new or upgraded software. Assist with strategic decisions on new systems. Generate reports from single or multiple systems.       Troubleshoot the reporting database environment and associated reports.       Identify and recommend new ways to streamline business processes       Illustrate data graphically and translate complex findings into written text.       Locate results to help clients make better decisions. Solicit feedback from clients and build solutions based on feedback.   Train end users on new reports and dashboards. Set FAST goals and provide feedback on FAST goals of repartees

Measures of Outcomes:

      Quality - number of review comments on codes written       Data consistency and data quality.       Number of medium to large custom application data models designed and implemented       Illustrates data graphically; translates complex findings into written text.       Number of results located to help clients make informed decisions.       Number of business processes changed due to vital analysis.       Number of Business Intelligent Dashboards developed       Number of productivity standards defined for project Number of mandatory trainings completed

Outputs Expected:

Determine Specific Data needs:

Work with departmental managers to outline the specific data needs for each business method analysis project

Critical business insights:

Mines the business’s database in search of critical business insights; communicates findings to relevant departments.

Code:

Creates efficient and reusable SQL code meant for the improvement
manipulation
and analysis of data. Creates efficient and reusable code. Follows coding best practices.

Create/Validate Data Models:

Builds statistical models; diagnoses
validates
and improves the performance of these models over time.

Predictive analytics:

Seeks to determine likely outcomes by detecting tendencies in descriptive and diagnostic analysis

Prescriptive analytics:

Attempts to identify what business action to take

Code Versioning:

Organize and manage the changes and revisions to code. Use a version control tool for example git
bitbucket. etc.

Create Reports:

Create reports depicting the trends and behaviours from analyzed data

Document:

Create documentation for worked performed. Additionally
perform peer reviews of documentation of others' work

Manage knowledge:

Consume and contribute to project related documents
share point
libraries and client universities

Status Reporting:

Report status of tasks assigned Comply with project related reporting standards and processes

Skill Examples:

      Analytical Skills: Ability to work with large amounts of data: facts figures and number crunching.       Communication Skills: Communicate effectively with a diverse population at various organization levels with the right level of detail.       Critical Thinking: Data Analysts must review numbers trends and data to come up with original conclusions based on the findings.       Presentation Skills - facilitates reports and oral presentations to senior colleagues       Strong meeting facilitation skills as well as presentation skills.       Attention to Detail: Vigilant in the analysis to determine accurate conclusions.       Mathematical Skills to estimate numerical data.       Work in a team environment       Proactively ask for and offer help

Knowledge Examples:

Knowledge Examples

      Database languages such as SQL       Programming language such as R or Python       Analytical tools and languages such as SAS & Mahout.       Proficiency in MATLAB.       Data visualization software such as Tableau or Qlik.       Proficient in mathematics and calculations.       Efficiently with spreadsheet tools such as Microsoft Excel or Google Sheets       DBMS       Operating Systems and software platforms Knowledge regarding customer domain and sub domain where problem is solved

Additional Comments:

Data Analysis, Data Modelling, Excellent communication skills, Stakeholder management, Industry knowledge, Latest Research and technology ideas, Machine learning, Advanced Data science techniques As a Staff Data Scientist, you'll have the opportunity to • Drive data-derived insights across a wide range of retail divisions by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives • Direct the gathering of data, assess data validity and synthesize data into large analytics datasets to support project goals • Lead a team of Data Scientists, Data Analysts, Data Engineers to improve the Catalog Content Quality using advanced Machine Learning and Gen AI. • Utilize big data analytics and advanced data science techniques to identify trends, patterns, and discrepancies in data. Determine additional data needed to support insights • Build and train AI/ML models for replication for future projects • Deploy and maintain the data science solutions • Communicate recommendations to business partners and influence future plans based on insights Your Responsibility • Consult with business stakeholders regarding algorithm-based recommendations and be a thought-leader to develop these into business actions. • Guides data scientists and senior data scientists across the domain DS team to ensure on-time delivery of ML products • Lead multiple complex ML products and guide senior tech leads in the domain in efficiently leading their products. • Proactive identification of complex business problems that can be solved using advanced ML and Computer Vision, finding opportunities and gaps in the current business domain • Evaluates proposed business cases for projects and initiatives • Translates business requirements into strategies, initiatives, and projects and aligns them to business strategy and objectives, and drives the execution of deliverables • Sets relevant deliverables based on the established success criteria and define key metrics to measure progress and effectiveness of the solution • Quantifies business impact and ensures regular impact measurement of all ML products in the domain. • Identifies and reviews model evaluation metrics based on analytical requirements • Ensures testing information is documented and maintained by the team • • Utilize product mindset to build, scale and deploy holistic data science products after successful prototyping • Demonstrate incremental solution approach with agile and flexible ability to overcome practical problems • Articulate and present recommendations to business partners and influence plans based on insights • Partner and engage with associates in other regions for delivering the best services to customers around the globe • Work with the customer-centric mindset to deliver high-quality business-driven analytic solutions. • Drive innovation in approach, method, practices, process, outcome, delivery, or any component of end-to-end problem solving • • Promote and support company policies, procedures, mission, values, and standards of ethics and integrity Our Ideal Candidate You are a technically strong and high-performing individual with excellent communication skills, a proven analytical skillset, and customer focus. You stay updated with the latest research and technology ideas and have a passion for utilizing innovative ways to solve problems. You are a good storyteller and able to articulate the intricacies of your models and explain your results clearly to stakeholders. In addition, you have industry knowledge of the retail space, with a keen interest in keeping up to date on the latest happenings in this space. Your Qualifications • Bachelor's with ? 10 years /Masters ? 8 years /Ph.D. in Comp Science/Statistics/Mathematics/Quantitative discipline with ? 5 years of relevant experience. Educational qualifications should be Computer Science/Statistics/Mathematics