Data Scientist/Principal Consultant
Job Location – Hyderabad | Position – Full-Time
People Involvement – IC, Product Development Team.
Skills (Must Haves):
10+ years of experience in analytics, preferably –
- 5+ years of experience in data science teams. Academic projects will not be counted. POC will not be counted. Kaggle competitions will not be counted.
- Strong statistical background with bachelor’s or Masters in Maths, Stats.
- Minimum 3-5 Projects in productions/development should be in production during tenure.
Primary –Statistical Modelling and Machine Learning – Full Stack development.
Secondary – Deep Learning Architectures – Machine Learning & NLP.
- Hands on with integration with connection to, DBMS, Hadoop file structures etc. experience connecting these to visual tools.
- Strong knowledge of social media analytics and external databases on data acquisitions.
- Business Analytics using Tableau, Power BI, Einstein Analytics, or any Py/R library
- Only experienced production staff of 3-5 years should apply. POC work will not be applicable for this role.
- Strong inclination of Statistics and mathematics with a focussed business acumen,
- Supervised and Unsupervised learning algorithms.
- Should be strong in parametric approaches and machine learning concepts.
Machine Learning Problems
- Forecasting, Univariate, and multivariate T+3 periods ahead.
- Binary Predictions.
- Continuous predictions.
- Unsupervised problems.
- NLP based predictions.
- Sentiment Analysis.
- Very strong statistical modelling with an outlier of EDA.
Deliver Features as identified in respective scrums for the development products with agreed accuracy in production.
- Successful delivery of the use cases POC’s as identified by the business requirements.
- Train and mentor junior staff, aspiring data scientists.
- Manage the SQL data bases and converse with AWS.
- Maintain the SQL Jobs, and analytical data marts.
- Publish the quality reports, manage the development lifecycle with team members.
- Identify KPI’s, talk to customers, domain experts and identify the story line.
- Build inferential charts, some common charts.
- Box Plots
- SQC Charts
- Advanced charts
- Manage, guide and mentor a team of juniors.
- Stakeholder management – 20-30%
- Client Engagement – 20-30%
- Work with AWS team to deploy solutions.
- Build machine learning pipelines and deploy the model in production.
- Train and monitor the model/feature to the implementation team structurally.
- Enhance customer experience by minimizing the deployment time.
- Technical capability of customizing the product as per customer need.
- R (20%) or Python (80%), should upskill in R.
- R Shiny Dev, Py Django or Flask or Dash + Server Management.
- Tensor-flow, keras, framework.