Data Scientist I

**Summary**:
Understand complex and critical business problems from Country/Regional/Global business functions, formulate integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to discover actionable insights and automate process for reducing effort and time for repeated use. High agility to be able to work across various business domains (commercial, NTO, GDD, NIBR, NBS) or divisions (Onco, GenMeds, Sandoz). Able to use business presentations, smart visualization tools and contextual storytelling to translate findings back to business users with a clear impact. No direct team management.

**About the Role**:
**Data Scientist I**

**Location - Hyderabad #LI Hybrid**

**Major accountabilities**:

- Develop automation for repeatedly refreshing analysis and generating insights Collaborates with globally dispersed internal stakeholders and cross-functional teams to solve critical business problems and deliver successfully on high visibility strategic initiatives
- Understand life science data sources including sales, contracting, promotions, social me-dia, patient claims and Real-World Evidence.
- Quickly learn the use of tools, data sources and analytical techniques needed to answer a wide range of critical business questions
- Articulate solutions/recommendations to business users. Works with senior data science team member to present analytical content concisely and effectively
- Manage own tasks and work with allied team members; plans proactively, anticipates and actively manages change, sets stakeholder expectations as required, identifies operational risks and independently drives issues to resolution, minimizes surprise escalations
- Has high learning agility and diligently follows updates in industry and area of work.
- ** Essential Requirements**:

- Quality of insights generated, and solutions provided, with quantified business impact / ROI
- Effective communication with Country/Regional/Global stakeholders
- Executes agreed targets for self
- Define and execute development plans for potential Subject Matter Experts
- Find creative ways to build team capabilities and play a direct role in driving a culture of innovation
- Values and Behaviors: in line with leadership standards of Novartis
- ** Education**:PhD or Masters (or bachelor’s from a top Tier University) in a quantitative discipline (e.g. Statistics, Economics, Mathematics, Computer Science, Bioinformatics, Ops Research, etc.)**Experience**:

- 7+ years of relevant experience in Data Science. In case of PhD, 4+ years post qualification experience. Experience in commercial pharma would be a bonus**.**:

- Extensive experience required in: Statistical and Machine Learning techniques like Regression (esp., GLM, non-linear, etc.), Classification (CART, RF, SVM, GBM, etc.) Clustering, Design of Experiments, Monte Carlo Simulations, Statistical Inference, Feature Engineering, Time Series Forecasting, Text Mining and Natural Language Processing
- Good to have skills: Stochastic models, Bayesian Models, Markov Chains, Dynamic Programming and Optimization techniques, Deep Learning techniques on structured and un-structured data, Recommender Systems (content and collaborative filtering), etc.
- Tools and Packages: SAS, R, Python, SQL. Exposure to dashboard or web-apps building using Qliksense, R-Shiny, Flask, etc. would be an added advantage.

**Commitment to Diversity and Inclusion**:
Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.

Division

US

Business Unit

Innovative Medicines

Location

India

Site

Hyderabad (Office)

Company / Legal Entity

IN10 (FCRS = IN010) Novartis Healthcare Private Limited

Functional Area

Data and Digital

Job Type

Full time

Employment Type

Regular

Shift Work

No

**Accessibility and accommodation**:
Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.