Data Scientist I jobs in Pune at UST

Role Proficiency

Job Description

Under supervision leverage data to arrive at business solutions and creates prototypes of the solution to define analytics roadmap for clients thereby bringing in business to the organization.

Outcomes

Work with stakeholders and creates quick prototypes of the solution to define analytics roadmap.
Work with business to understand business domain and convert business problems into analytics problem
Create or use existing frameworks to test and validate new models
Explain models and put results in easy to interpret manner such that non-analytic person can understand
Turn data into information that can improve current workflow or processes that will help to make better business decisions. Generate business insights to help clients with decision making.
Adhere to best practices of coding
Set FAST goals and provide feedback on FAST goals of reportees

Measures Of Outcomes

Schedule Adherence
Quality of code and other deliverables
Number of reusable components developed
Number of new analytics solutions that got approved for further development

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

Visualizing/presenting 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 a version control tool like 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

Create reports depicting the trends and behaviours from the analysed data
Training end users on new reports and dashboards.
Set FAST goals and provide feedback to FAST goals of mentees

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 client universities

Status Reporting

Report status of tasks assigned
Comply to project related reporting standards/process

Solution Architecture

Create modular architecture such that it can be reused easily across projects.

Analysis

Report trends for anomalies outliers trend changes and opportunities from a given data set

Data Gathering

Partner with business and gather relevant data

Modelling

Data models and experiments for solving business problems

Stakeholder Management

Explain findings to both technical and nontechnical stakeholder.

New Business Development

Create solution architecture and quick prototypes to explain analytics roadmap to a business team.

Team Management

Increase team productivity by upskilling them technically.

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.
Ability to work with structured semi-structured and unstructured datasets.
Ability to learn and implement new Data Science algorithms in a fast turnaround time
Analytical Skills: Ability to work with large amounts of data: facts figures and number crunching.
Communication Skills: Communicate effectively with diverse people at various organization levels with the right level of detail.
Critical Thinking: Data analysts must look at the 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
Ask proactively for help and offer help proactively
Break big problem into small components and define the solution architecture.
Explains complex models (like CNN RNN XGBoost etc.) in a manner which is easy to understand for a nontechnical stakeholder.
Have good understanding of known data science tools and technology like H20 Neo4j PySpark etc.

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 on atleast 1 version control tool like git bitbucket
Have experience working with project management tool like Jira
Data Science based high performance application development knowledge is required.
NLP and Computer Vision tools and libraries – OpenCV spaCY Transformers Attention models etc.