Data Scientist - Time Series Forecasting

Job Role - Data Scientist

Location - Bangalore (Onsite)

3 to 6 month Contract to hire

Contract to Hire

Immediate Joiners only

Must Have Skills : Python, Machine Learning, Time series Forecasting, data bricks, exposure to GitHub and versioning, and Communication.

Job Responsibilities :

- This role will lead technical development within Artificial Intelligence/Machine Learning for Advanced

Analytics. This will include design, implement, and maintain digital solutions.

- Set up and manage our AI development and facilitate production infrastructure.

- Help AI product managers and business stakeholders understand the potential and limitations of

AI when planning new products.

- Build data ingest and data transformation infrastructure.

- Identify transfer learning opportunities and new training datasets.

- Build AI models from scratch and help product managers and stakeholders understand results.

- Deploy AI models into production.

- Create APIs and help business customers put results of your AI models into operations.

- Keep current of latest AI research relevant to PBNA business domain.

- Technical subject matter expert for Advanced Analytics and digital solution (AI, ML, Advanced Analytics)

- Develop proof-of-concept demos in a SAFe Agile team.

- Identify transfer learning opportunities and new training datasets.

- Build and deploy AI models for PBNA

- Assess new capabilities within AI/ML, shape business demand to leverage digital capabilities.

- 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.

- 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 works 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.

Requirements & Qualifications :

- PhD or Masters (or Bachelors from a top Tier University) in a quantitative discipline (e.g. Statistics, Economics, Mathematics, Computer Science, Bioinformatics, Ops Research, etc.)

- 7+ years of relevant experience in Data Science. In case of PhD, 5+ years post qualification experience.

- Hands-on experience in Statistical Modelling, Machine Learning, Deep Learning and Data Mining

techniques .

- Experience working in Text Analytics, NLP

- 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 (NLP).

Good to have skills :

- Stochastic models, Bayesian Models, Markov Chains, Dynamic Programming and

- Optimization techniques, Deep Learning techniques on structured and unstructured 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 added advantage.

- Exposure to Azure

- Experience building AI models in platforms such as Keras, TensorFlow, or Theano.

- Experience in managing teams and leadership skills.

- Excellent client facing skills along with prior demonstrated experience of leading teams at various stages.

- Should demonstrate a team oriented and collaborative approach, and excellent communication skills,
including strong oral and written communication capabilities

- Demonstrated commitment to learning about AI through your own initiatives through courses, books, or side projects.

- Ability to work with virtual teams (remote work locations); lead team of technical resources (employees and contractors) based in multiple locations across geographies

- Participate in ideation and solutioning discussions, driving clarity of complex issues/requirements to
build robust solutions.