Lead I - Data Science

November 27, 2025

Role Description Role Proficiency: Provide expertise on data analysis techniques using software tools. Under supervision streamline business processes. Outcomes <ul><li> Design and manage the reporting environment; which include data sources security and metadata.</li><li> Provide technical expertise on data storage structures data mining and data cleansing.</li><li> Support the data warehouse in identifying and revising reporting requirements.</li><li> Support initiatives for data integrity and normalization.</li><li> Assess tests and implement new or upgraded software. Assist with strategic decisions on new systems. Generate reports from single or multiple systems.</li><li> Troubleshoot the reporting database environment and associated reports.</li><li> Identify and recommend new ways to streamline business processes</li><li> Illustrate data graphically and translate complex findings into written text.</li><li> Locate results to help clients make better decisions. Solicit feedback from clients and build solutions based on feedback.</li><li> Train end users on new reports and dashboards.</li><li>Set FAST goals and provide feedback on FAST goals of repartees </li></ul>Measures Of Outcomes <ul><li> Quality - number of review comments on codes written</li><li> Data consistency and data quality.</li><li> Number of medium to large custom application data models designed and implemented</li><li> Illustrates data graphically; translates complex findings into written text.</li><li> Number of results located to help clients make informed decisions.</li><li> Number of business processes changed due to vital analysis.</li><li> Number of Business Intelligent Dashboards developed</li><li> Number of productivity standards defined for project</li><li>Number of mandatory trainings completed </li></ul>Outputs Expected Determine Specific Data needs: <ul><li>Work with departmental managers to outline the specific data needs for each business method analysis project </li></ul>Critical Business Insights <ul><li>Mines the business’s database in search of critical business insights; communicates findings to relevant departments. </li></ul>Code <ul><li>Creates efficient and reusable SQL code meant for the improvement manipulation and analysis of data.</li><li>Creates efficient and reusable code. Follows coding best practices. </li></ul>Create/Validate Data Models <ul><li>Builds statistical models; diagnoses validates and improves the performance of these models over time. </li></ul>Predictive Analytics <ul><li>Seeks to determine likely outcomes by detecting tendencies in descriptive and diagnostic analysis </li></ul>Prescriptive Analytics <ul><li>Attempts to identify what business action to take </li></ul>Code Versioning <ul><li>Organize and manage the changes and revisions to code. Use a version control tool for example git bitbucket. etc. </li></ul>Create Reports <ul><li>Create reports depicting the trends and behaviours from analyzed data </li></ul>Document <ul><li>Create documentation for worked performed. Additionally perform peer reviews of documentation of others' work </li></ul>Manage Knowledge <ul><li>Consume and contribute to project related documents share point libraries and client universities </li></ul>Status Reporting <ul><li>Report status of tasks assigned</li><li>Comply with project related reporting standards and processes </li></ul>Skill Examples <ul><li> Analytical Skills: Ability to work with large amounts of data: facts figures and number crunching.</li><li> Communication Skills: Communicate effectively with a diverse population at various organization levels with the right level of detail.</li><li> Critical Thinking: Data Analysts must review numbers trends and data to come up with original conclusions based on the findings.</li><li> Presentation Skills - facilitates reports and oral presentations to senior colleagues</li><li> Strong meeting facilitation skills as well as presentation skills.</li><li> Attention to Detail: Vigilant in the analysis to determine accurate conclusions.</li><li> Mathematical Skills to estimate numerical data.</li><li> Work in a team environment</li><li> Proactively ask for and offer help </li></ul>Knowledge Examples Knowledge Examples <ul><li> Database languages such as SQL</li><li> Programming language such as R or Python</li><li> Analytical tools and languages such as SAS & Mahout.</li><li> Proficiency in MATLAB.</li><li> Data visualization software such as Tableau or Qlik.</li><li> Proficient in mathematics and calculations.</li><li> Efficiently with spreadsheet tools such as Microsoft Excel or Google Sheets</li><li> DBMS</li><li> Operating Systems and software platforms</li><li>Knowledge regarding customer domain and sub domain where problem is solved </li></ul>Additional Comments <ul><li> 5-10 years’ experience in data science/AI-ML/Generative AI development.</li><li> Prior hands-on experience in developing complex AI/ML solutions as an AI/Data Scientist or Engineer, in both proof of concept and production environments</li><li> Strong knowledge of Machine Learning, Deep Learning, Generative AI/LLMs, and various use cases.</li><li> Ability to apply methods such as predictive analytics, time series analysis, hypothesis testing, classification, clustering, and regression analysis.</li><li> Strong background in statistics and probability, including experience with descriptive and inferential statistical analysis.</li><li> Proficient in a core programming language such as Advanced Python, JavaScript's/ React/Angular, Scala, Spark</li><li> Experience with one or multiple databases like SQL server, Postgres, Click house, Presto</li><li> In-depth understanding of Cloud Platforms such as AWS, GCP, Azure, and ML platforms like Sage Maker.</li><li> Familiarity with Visualization Tools like Tableau, PowerBI</li><li> Experience in discovering use cases, scoping, and delivering complex solution architecture designs to diverse audiences, adapting technical depth as needed.</li><li> Understanding of DataOps, MLOps, LLMOps, Observability, DevOps, and SRE concepts.</li><li> Master’s or Bachelor’s degree in Data Science, Computer Science, or a relevant field.</li><li> Strategic thinker with excellent analytical and problem-solving skills.</li><li> Strong communication skills, able to drive results & capable of interacting/collaborating with both business decision-makers and other AI/ML experts/coders. </li></ul>Skills Data Science,Artificial Intelligence,Machine Learning

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