Philips - Manager - Data Science

Data Science Manager

- Royal Philips (NYSE: PHG, AEX: PHIA) is a leading health technology company focused on improving people's health and enabling better outcomes across the health continuum from healthy living and prevention, to diagnosis, treatment and home care. Philips leverages advanced technology, deep clinical, and consumer insights to deliver integrated solutions.

- Headquartered in the Netherlands, the company is a leader in diagnostic imaging, image-guided therapy, patient monitoring and health informatics, as well as in consumer health and home care. Philips' health technology portfolio generated 2017 sales of EUR 17.8 billion and employs approximately 74,000 employees with sales and services in more than 100 countries.

Responsibilities :

- Analyzes, measures, and facilitates optimization of our marketing return on investments and tactics across multiple channels. Drive excellent practices and technical standards for establishing KPIs and goals for Marketing, developing information suites (Dashboards, reports, visualizations) fit for C-level consumption, and marketing campaign tracking and measurement.

- Leverage machine learning models to address key growth challenges such as lifecycle marketing, predictive LTV, cross-channel spend allocation, response modelling, campaign/channel performance measurement methodologies, Program effectiveness and media attribution.

- Develop and improve marketing mix and A&P models and frameworks to assign credit for traffic and conversions across a variety of Marketing channels and touchpoints.

- Leverage Philips- data to scale our ability to optimize marketing across the customer journey to optimize return on investment through analysis, modelling, experiments and pre-post analyses.

- Develop and implement marketing data management practices

- Ability to use data for Exploratory, descriptive, Inferential, Prescriptive, and Advanced Analytics - Mandatory

- Ability to share dashboards, reports, and Analytical insights from data - Mandatory

Technical Knowledge and Skills required :

- Econometrics, Market mix modeling, some Operations research and affinity modeling experience is mandatory

- Track record in delivering strong and impactful; competitor and market tracking insights

- High affinity with applying new IT platforms / dash boarding software tools for reporting and Experience in a consumer focused, complex, matrixed, multinational environment, e.g. consumer goods, online services, e-commerce, or mobile applications

- Competitor insight generation

- Strong background into Database design, modeling and architecture - preferred Fluency in web analytics and deep technical understanding of how data are created from first party and third-party web beacons

- Proficiency with R and/or Python libraries commonly used in data science

Soft Skills Required :

- Good communication and presentation skills

- Highly driven, energetic, flexible, resourceful & ability to multitask

- Clarity of thoughts and vision

- Ability to ideate and bring solutions to the table

- Adherence to timelines, without sacrificing quality of output

- Hands on and detail oriented, with a strong ability to co-ordinate across different Geographies and with different stakeholders at Exec and Director levels

- Straightforward, honest and succinct communicator. Can organize, clarify and communicate complex ideas quickly, succinctly and accurately.

- Creative. Demonstrated ability to think innovatively- connecting the dots where others cannot when it comes to consumer/ customer and user data to create business building insights

Work Experience :

- Minimum 8-11 years of increasingly responsible experience in high impactful marketing analytics individual contributor roles

- Can be from e-Commerce companies like Amazon, Flipkart etc.

- In depth knowledge of multivariate statistical techniques including marketing mix modeling, attribution modelling, TURF, RAD, clustering, churn, customer scoring, neural networks amongst others

- High affinity with AI powered insight tools and engines and application of data science to marketing problems

- Rich experience in Marketing analytics with a strong understanding of the full range of online marketing channels, how they work, how they can be integrated, and how to evaluate them

Academics :

- Master's degree in a quantitative discipline, e.g., Math, Statistics, Physics, Operations Research, Economics, Econometrics

- MBA /BTech-BE from IIT/NITs or Tier 1 engineering schools only,, MS Analytics from Tier 1 schools; special preference to MBA from Mudra Institute of Communication, Ahmedabad or MBA schools that excel in Marketing

- Strong exposure to Statistics - Predictive Analytics - Mandatory