Specialist II - Data Science

0 years

0 Lacs

Posted:1 week ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

Role Description

Role Proficiency:Independently develop data-driven solutions to difficult business challenges by utilize analytical statistical and programming skills to collect analyze and interpret large data sets under supervision.

Outcomes

  • Work with stakeholders throughout the organization to identify opportunities for leveraging data from our customers to make models that can generate business insights
  • Create new experimental frameworks or build automated tools to collect data
  • Correlate similar data sets to find actionable results
  • 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.
  • Develop Data Visualization and illustrations on given business problem
  • Use predictive modelling to increase and optimize customer experiences and other business outcomes.
  • 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.
  • Number of Business Intelligent Dashboards developed
  • Number of productivity standards defined for project
  • Number of Prediction and Modelling models used
  • Number of new approaches applied to understand the business trends
  • Quality of data visualization done to help non-technical stakeholders comprehend easily.
  • Number of mandatory trainings completed

Outputs Expected

Statistical Techniques:
  • Apply statistical techniques like 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

  • Oversees 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 the relevant departments.

Code

  • Creating 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.

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

Create Reports

  • Creates reports depicting the trends and behaviours from the analysed data
  • Training end users on new reports and dashboards.

Document

  • Create documentation for own work as well as perform 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 to new conclusions based on the findings.
  • Strong meeting facilitation skills as well as presentation skills.
  • 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 and have strong interpersonal skills to work in collaborative environment
  • Proactively ask for and offer help

Knowledge Examples

Knowledge Examples
  • Programming languages – Java/ Python/ R.
  • 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.
  • Spreadsheet tools such as Microsoft Excel or Google Sheets
  • DBMS
  • Operating Systems and software platforms
  • Knowledge about customer domain and about sub domain where problem is solved
  • Proficient in at least 1 version control tool like git bitbucket
  • Have experience working with project management tool like Jira

Additional Comments

Must have -Statistical Concepts, SQL, Machine Learning (Regression and Classification), Deep Learning (ANN, RNN, CNN), Advanced NLP, Computer Vision, Gen AI/LLM (Prompt Engineering, RAG, Fine Tuning), AWS Sagemaker/Azure ML/Google Vertex AI, Basic implementation experience of Docker, Kubernetes, kubeflow, MLOps, Python (numpy, panda, sklearn, streamlit, matplotlib, seaborn)

Skills

Data Management,Data Science,Python

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