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 reporteesMeasures 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 completedOutputs Expected:
Statistical Techniques:
Apply statistical techniques for example regressionproperties 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:
simulation
scenario analysis
modelling
etc.
Data Visualization:
Business Objects
D3
ggplot
etc.
Management and Strategy:
Critical business insights:
Code:
manipulation
and analysis of data.
Version Control:
bitbucket
etc.
Prescriptive analytics:
Create Reports:
Document:
Manage knowledge:
share point
libraries and client universities
Status Reporting:
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 helpKnowledge Examples:
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 JiraAdditional Comments:
Scala + Spark + AWS/any cloud · Design and deliver scalable web services, APIs, and backend data modules. · Experience in writing multithreaded programs running in Scala/Spark. · Experience with Git and building tools like Gradle/Maven/SBT. · Strong understanding of object-oriented design, data structures, algorithms, profiling, and optimization. · Knowledge of top algorithms like sorting, heap/stack, queue, search, etc. · Familiarity with test-driven development · Thrive in a fast-paced environment, with the ability to deliver code of quality quickly. · Attention to detail. Strong communication and collaboration skills. · Understand requirements and develop reusable code using design patterns & component architecture and write unit test cases. · Collaborate with product management and engineering teams to elicit and understand the requirements and develop solutions. · Stay current with the latest tools, technology ideas, and methodologies; share knowledge by clearly articulating results and ideas to key decision-makers.