1. Hiring For Azure ML – Data scientist
Tata Consultancy Services Ltd
Job description
Years of exp : 4- 8 Years
Location : PAN INDIA
- Develops analytical / Data Science model for prioritized use case ensuring learning and automation opportunities.
- Command over analytics model development process:
- Business & Data Understanding, Data Preparation, Model Development, Validation and Deployment
- Expertise and Experience in Microsoft Azure Platform, Python / Pyspark, AI/ML, ML Ops, DevOps
Role: Manager – Data Science
Industry Type: IT Services & Consulting
Functional Area: Data Science & Analytics
Employment Type: Full Time, Permanent
Role Category: Data Science & Machine Learning
2. Data Scientist (healthcare)
Company Name: Santechture
5 – 10 years
Not Disclosed
Job description
- 5+ years of work experience in healthcare big data projects, out of which 2 years in a senior level role is a must.
- Any Healthcare experience is a must for this role, preferably US Healthcare/UAE Healthcare.
- Must be conversant with Natural Language Processing, Machine learning, Conceptual modelling, Statistical analysis, Predictive modelling, Hypothesis testing.
- Experience working on building an AI Conversation Voice Chatbot, NLP, NLU, Multilingual, Speech Recognition, Text to Speech and Speech to Text Conversion.
- Worked on ANN, CNN, RNN, deep learning preferably in Digital Health startup to solve the specific complex problem.
- Good experience in Artificial Neural Network (ANN ), AI conversational Chatbot & Needs to be able to write the required Algorithm and coding programming.
- Experience in different programming languages such as Python, Tensor Flow, Keras, AWS (ML and DL), Numpy, Pytorch.
- Needs to have statistical, mathematical, predictive modeling as well as business strategy skills to build the algorithms necessary to ask the right questions and find the right answers.
- Need to understand how the products are developed and even more important, as big data touches the privacy of consumers, they need to have a set of ethical responsibilities.
- Experience or exposure to Healthcare Medical Billing Claims Management is preferred
- Experience in hospital operations and a general understanding of revenue cycle with an emphasis on billing, coding and charge capture desirable.
- Familiarity with Rule Edits or Business Rules Management Systems technologies and tools is an advantage.
Role: Data Scientist
Industry Type: Software Product
Functional Area: Data Science & Analytics
Employment Type: Full Time, Permanent
Role Category: Data Science & Machine Learning
3. Associate Data Scientist – Retail
Shell India Markets Private Limited
3 – 8 years
Not Disclosed
Job description
The Role
General Position Definition
- Incumbent is responsible for developing analytical models for projects collaborating with different business stakeholders & other partners and working across a range of technologies and tools.
- The ideal candidate has strong background in quantitative skills (like statistics, mathematics, advanced computing, machine learning) and has applied those skills in solving real world problems across different businesses / functions.
Purpose
- Develops analytics models using specialized tools based on the business problem and data available
- Identifies the right set of models and develops the right code / package to execute them
- Evaluates the validity of the model (both scientifically as well as from a business perspective)
- Support the Data Science Team Lead in design and execution of analytics projects
- Work with Shell stakeholders and subject matter experts to complete tasks and deliverables on projects
Skills
Stakeholder Engagement Skills
- Working collaboratively across multiple sets of stakeholders – business SMEs, IT, Data teams, Analytics resources, etc. to deliver on project deliverables and tasks
- Identify actionable insights that directly address challenges / opportunities
- Articulate business insights and recommendations (based on model output) to respective stakeholders
- Understanding business KPI’s, frameworks and drivers for performance
- Proficiency Level:Skill
Education Requirement/Field of Study :
- 3+ years of relevant experience in Retail domain
- Advanced university degree in Mathematics, Statistics, Engineering, Economics, Quantitative Finance, OR, etc.
- Good interpersonal communication skills and influencing skills
- Eagerness to learn and ability to work with limited supervision
Requirements :
Industry / Functional Expertise
- Provide deep business expertise preferably Oil & Gas – Upstream or Downstream businesses. (If these are not available, willing to consider other industries that are similar or related – manufacturing, mining, power generation, etc.)
or
functional expertise in any one or more of the following industry / functional areas
- Customer / Marketing– pricing analytics, churn prediction, cross-sell / up-sell, Market Basket Analysis, Product Recommendation, Marketing Mix Modeling, Campaign design and effectiveness testing, Network Modeling, Customer segmentation, propensity analysis, customer lifetime value, profitability analysis, Customer experience (incl. voice of customer), CRM, Loyalty program management,
- Supply Chain / Spend: Demand & Supply Forecasting, Spend Analytics, Vendor Scoring, Pricing analysis (buy-side), product substitution analysis, product portfolio optimization, Tail spend analysis, logistics / network / route optimization, Contract Compliance
- Proficiency Level:Mastery
Modeling and Technology Skills
- Good expertise in machine learning techniques (supervised and unsupervised) statistics / mathematics / operations research including (but not limited to):Advanced Machine learning techniques: Decision Trees, Neural Networks, Deep Learning, Support Vector Machines, Clustering, Bayesian Networks, Reinforcement Learning, Feature Reduction / engineering, Anomaly deduction, Natural Language Processing (incl. Theme deduction, sentiment analysis, Topic Modeling), Natural Language Generation
and/or
- Statistics / Mathematics: Data Quality Analysis, Data identification, Hypothesis testing, Univariate / Multivariate Analysis, Cluster Analysis, Classification/PCA, Factor Analysis, Linear Modeling, Logit/Probit Model, Affinity & Association, Time Series, DoE, distribution / probability theory
and/or
- Operations Research: Sensitivity Analysis – Shadow price, Allowable decrease or increase, Transportation problem & variants, Allocation Problem & variants, Selection problem, Multi-criteria decision-making, models, DEA, Employee Scheduling, Knapsack problem, Supply Chain Problem & variants, Location Selection, Network designing – VRP, TSP, Heuristics Modeling
- Strong experience in specialized analytics tools and technologies (including, but not limited to)Python, Azure Analysis Services
- Spotfire, PowerBI
- Awareness of Data Bricks, Apache Spark, Hadoop
- Awareness of Agile / Scrum ways of working
Identify the right modeling approach(es) for given scenario and articulate why the approach fitsAssess data availability and modeling feasibilityReview interpretation of models resultsEvaluate model fit and based on business / function scenarioProficiency Level:Skill-to-Mastery
Special Challenges
- Rapid onboarding on projects, understanding analytics goal and working with ill-defined datasets
- Communicating technical jargon in plain English to colleagues within Data Science team and outside
- Virtual working with network of colleagues located throughout the globe
Role: Data Scientist
Industry Type: Petrochemical / Plastics / Rubber
Functional Area: Data Science & Analytics
Employment Type: Full Time, Permanent
Role Category: Data Science & Machine Learning