Data Scientist - Data & Analytics

Data Scientist - Data & Analytics

Position : Senior

Location : Bangalore

Roles and Responsibilities : Data Scientist Customer Analytics

The position requires a person to work on global engagements (US, Europe, APAC) in any consumer and retail specific area. The requirements are :

1. A desirable candidate should have led the project in field of customer analytics

2. Demonstrated ability in team mentoring, delivery management and client communication

3. The person holding this position is responsible for leading the solution development and implementing advanced analytical approaches across a variety of industries in the customer analytics

4. Guide data architects to prepare the relevant data marts with right analytical requirements

5. Proactively engage with business and other teams to discuss the models and analysis results

6. Documenting and presenting work to the client. Proactively generating insights and suggest business decision making

DOMAIN : Customer Analytics

1. Should have experience in analyzing customer sentiment & customer behavior using NLP tools & techniques

2. Should have experience on Propensity modelling, Customer churn analytics, Cross sell and Up sell analysis

3. In-depth knowledge and experience on marketing and campaign analysis

4. Identify and recommend opportunities for digital and CRM touchpoints

5. Should have experience in handling CLTV modeling

6. Should have hands on experience in developing statistical models for price elasticity, price guidance, margin optimization, media spend optimization, assortment analysis and transfer demand analysis and solutions

7. Experience working for any of the customer related datasets that like IRI POS data, invoicing data, CRM data

8. Experience in building price and promotion model, market mix model, media effectiveness, assortment analysis

II. Roles and Responsibilities: Data Scientist Supply Chain Analytics

The position requires a person to work on global engagements (US, Europe, APAC) in any supply chain specific area. The requirements are -

1. The Data Scientist will help lead, develop, and execute the framework for implementing predictive analytics and machine learning within the Global Supply Chain.

2. At this position you act as an interface between the delivery team and the supply chain team, effectively understanding the client business and supply chain. Candidates will be expected to lead projects across several areas related to Supply Chain

3. The person holding this position is responsible for leading the solution development and implementing advanced analytical approaches across a variety of industries in the supply chain domain.

4. Demonstrated ability in team mentoring, delivery management and client communication

5. Make business recommendations (e.g. cost-benefit, forecasting, experiment analysis) with effective presentations of findings to stakeholders through visual displays of quantitative information

6. Guide data architects to prepare the relevant data marts with right analytical requirements

7. Documenting and presenting work to the client. Proactively generating insights and suggest business decision making

Domain: Supply Chain Analytics

1. Working knowledge of Procurement analytics, Distribution/Logistics planning, Network planning and optimization. Demand forecasting, Inventory management, Linear Programming

2. A strong conceptual understanding of statistical and machine learning based models- regression, optimization, time series forecasting, bagging, boosting, neural networks, SVM, Clustering, Matrix Factorization

3. Development, calibration and recalibration of analytical models

Qualifications and Skill requirement

Must Have:

1. Candidate should have 3-8 years of experience in the field of customer analytics end-to-end modeling life cycle

2. Candidate must have a bachelors degree in any quantitative field or a BTech with significant analytics/machine learning experience

3. Experience with data retrieval manipulation, Storing and processing using one or more of Spark SQL, SparkML, Spark ML Pipeline, Spark API, Spark Datasets, RDD, Hive QL, Python, Hadoop

4. A strong quantitative background, excellent communication skills (written and verbal) and excellent presentation skills are necessary for the role.

5. Good logic building to create a solution and excellent programming skills in either Python, Pyspark, R, SAS to develop the models

6. A strong conceptual understanding of statistical and machine learning based models- regression, optimization, time series forecasting, bagging, boosting, neural networks, SVM, Clustering, Matrix Factorization

7. Should have experience on development, calibration and recalibration of analytical models

8. Should have experience in cloud and big data platform to get the models created and channelize it through digital platform

9. Proficiency in working and querying large data sets and understanding of insurance databases is must.

Good to Have:

1. Experience in cloud and big data platform (Azure, AWS, GCP) to get the models created and channelize it through digital platform

2. Machine Learning and Cognitive technologies: Azure Data bricks, Azure ML Studio, ML Services, ML Ops, MLFlow, KubeFlow, AWS, GCP

3. APICS-CPIM certification

4. Hands-on skills in using and implementing models in one or frameworks: TensorFlow, Scikit-learn, NLP algorithms

5. Good to have experience with real time streaming applications Kafka and web app development using Flask or Django

6. Experience in IoT, unstructured text, image data is an added advantage