Data Modeler

Role Proficiency: Develop data-driven solutions for difficult business challenges. Utilizing analytical statistical and programming skills to collect analyze and interpret large data sets with supervision. Outcomes: - Work with stakeholders throughout the organization to identify opportunities for leveraging data from our customers to create models that can generate business insights - Build predictive models and machine learning algorithms to analyse large amounts of information to discover trends and patterns. - Mine and analyse data from company databases to drive optimization and improvement of product development marketing techniques business strategies etc - Develop processes and tools to monitor and analyse model performance and data accuracy. - Coordinate with different functional teams to implement models and monitor outcomes. - Set FAST goals and provide feedback on FAST goals of reportees Measures of Outcomes: - Number of business processes changed due to vital analysis. - Models applied to Business Problems - Number of Business Intelligent Dashboards developed - Number of productivity standards defined for project - Number of mandatory trainings completed Outputs Expected: Statistical Techniques: properties of distributions statistical tests etc. to analyse data. Machine Learning Techniques: decision tree learning artificial neural networks etc. to streamline data analysis. Creating advanced algorithms: - Create advanced algorithms and statistics using regression simulation scenario analysis modelling etc. Data Visualization: - Visualize and present data for stakeholders using: Periscope Business Objects D3 ggplot etc. Management and Strategy: - Oversee the activities of analyst personnel and ensures the efficient execution of their duties. Critical business insights: - Mines the business’s database in search of critical business insights and communicates findings to relevant departments. Code: - Create efficient and reusable code meant for the improvement manipulation and analysis of data. Version Control: - Manages project codebase through version control tools e.g. git bitbucket etc. Prescriptive analytics: - Attempts to identify what business course of action to make Create Reports: - Creates reports depicting the trends and behaviours from the analysed data - Train end users on new reports and dashboards. Document: - Create documentation for personal work as well as performing a peer review 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 process Skill Examples: - Excellent pattern recognition and predictive modelling skills - Extensive background in data mining and statistical analysis - Expertise in machine learning techniques and creating algorithms. - 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 look at numbers trends and data and come up with new conclusions based on the findings. - Attention to Detail: Making sure to be vigilant in the analysis to come to correct conclusions. - Mathematical Skills to estimate numerical data. - Work in a team environment - Proactively ask for and offer help Knowledge Examples: - Programming languages - Java/ Python/ R / Scala - Web Services - Redshift S3 Spark DigitalOcean etc. - Statistical and data mining techniques: GLM/Regression Random Forest Boosting Trees text mining social network analysis etc. - Google Analytics Site Catalyst Coremetrics Adwords Crimson Hexagon Facebook Insights etc. - Computing Tools - Map/Reduce Hadoop Hive Spark Gurobi MySQL etc. - Database languages such as SQL NoSQL - Analytical tools and languages such as SAS & Mahout. - Practical experience with ETL data processing etc. - Proficiency in MATLAB. - Data visualization software such as Tableau or Qlik. - Proficient in mathematics and calculations. - Utilization of 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 - Proficient in at least one version control tool like git bitbucket - Have experience working with project management tool akin to Jira Additional Comments: