Specialist I - Data Science

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:

• Apply statistical techniques for example regression
  

properties of distributions
statistical tests
etc. to analyse data.
Machine Learning Techniques:

• Apply machine learning techniques like clustering 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.

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  Mathematical Skills to estimate numerical data.
• Work in a team environment
• Proactively ask for and offer help
  

Knowledge 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 Jira
  

Additional Comments
Data Scientist:

• 5+ years of experience in AI, Generative AI, and Machine Learning.
• Proficiency in mandatory skills, including Machine Learning, Python, Keras, and Big Data.
• Strong knowledge of Generative AI technologies, such as GPT-3, GANs, and Transformers such as BERT and T5).
• Proficient in Python programming and data science libraries like Pandas.
• Experience in deploying data-driven solutions in cloud environments.
• Apply advanced machine learning techniques and models to solve complex business problems, with a focus on generative AI.
• Utilize expertise in Machine Learning, Kafka, Big Data, Python, Keras, Pandas, and Time Series analysis to develop predictive models and gain insights from large datasets.
• Lead data engineering efforts to ensure efficient data collection, storage, and transformation.
• Collaborate with cross-functional teams to understand business needs, design AI-powered solutions, and drive their implementation.
• Stay updated with the latest developments in Generative AI and integrate new techniques and models into our projects.
• Experienced in Synthetic Data Generation to enhance data augmentation strategies for model training and testing.
• Utilize your knowledge of Cloud Environments (AWS, Azure, GCP) to optimize the scalability and deployment of AI models.-
• Excellent problem-solving, communication, and collaboration skills. **Qualifications:**
• Bachelors degree in Computer Science, Data Science, or a related field.