Sapient is looking for a Manager, Data Science to join its Data Science practice. The role is to not only be a trusted advisor to our clients for driving the next generation innovation in applied machine learning and statistical analysis, but also a leader in advancing the group’s capabilities into the future
As part of the team, you will be responsible for leading teams that create data driven solutions that at the core are driven by relevant learning algorithms. In this role you will educate internal and external teams on conceptual models for problem solving in the machine learning realm and help translate goals and objectives into data driven solutions. You will enjoy working with some of the most diverse data sets in the world, cutting edge technology, and the ability to see your insights turned into real business
results on a regular basis
The role is critical in helping advance the application of machine learning as a core building block to core market offerings in eCommerce, advertising, adtech and business transformation. In addition, you will be responsible for directing analysis that informs and improves the effectiveness of the planning, execution and optimization of marketing tactics.
As an evangelist for data science, you will partner with leaders in various divisions, industries and geographies, in order to ensure that increasingly more solutions we bring to the market are data driven and are supported by a strong data sciences group.
Core areas of focus for this group includes applications in customer segmentations, media and advertising optimization solutions, developing recommender systems, fraud analytics, personalization systems and forecasting.
- Design and implement high performance and robust analytical models in support of product and project objectives
- Research and bring innovations to develop next generation solutions in core functional areas related to digital marketing & customer experience solution blocks - Content and Commerce , AdTech, Customer Relationship Management (CRM), Campaign Management
- Provide technical thought leadership, coaching and mentorship in the field of data science in working with engineering and other cross functional teams
- Evolve the approach for the application of machine learning/deep learning to existing program and project disciplines
- Design controlled experiments to measure changes to new user experience
- Segment customers and markets to improve targeting and messaging of product recommendations and offers
- Direct research and evaluation for open source and vendor solutions in the analytics platforms space to guide solutions
- Be responsible for solution and code quality including providing detailed and constructive design and code reviews
- Help establish standards in machine learning and statistical analysis to ensure consistency in quality across projects and teams and identify relevant process efficiencies
- Assess client needs and requirements to ensure your team is adopting the appropriate approach to solve client challenges
- BS/MS in Computer Science, Math, Physics, Engineering, Statistics or other quantitative or computational field. Advanced degrees preferred
- Demonstrate proficiency with various approaches in regression, classification, and cluster analysis
- Demonstrate proficiency in deep learning.
- Must have experience ML models in R/ Python
- Demonstrable strength in programming in Python/R/Scala
- Experience with one or more data visualization tool / library such as Tableau, R Shiny, Seaborn, etc.
- Good understanding of applied statistics, such as probability distributions, measures of dispersion and central tendency, hypothesis testing and statistical inferences.
- Expertise in SQL programming languages and familiarity with Hive, PIG
- Demonstrated Experience in at least in one of the following NLP/computer vision/operations research/data mining/ML/AI
- Experience working in a Unix/Linux environment for automating processes with shell scripting
- Excellent quantitative skills and the ability to tell a story using data
- Strong communication and presentation skills
- Ability to initiate and drive projects from conception to completion with minimal guidance
- Passionate about turning data into actionable insights
- Proven ability to perform in-depth analysis, compile and interpret results
- Ability to differentiate and apply models on the problem statement
- Should Know what model to apply and in what situation to apply (know advantages and dis advantages of ML /DL techniques)
Good to Have
- Ph.D. in Computer Science, Math, Physics, Engineering, Statistics or other quantitative or computational field
- Expertise in application of machine learning algorithms on large datasets
- Experience with large datasets and distributed computing (Hadoop, Spark) a plus
- Experience accessing data, map-reduce programming style and training models in Hadoop, Spark
- Experience in deploying models in cloud platforms such as Google Cloud/Microsoft Azure/AWS is a plus
- Nice to have knowledge of NoSQL DBs like MongoDB, Cassandra and HBase
- Contribution to research community reflected in publications in top conferences/Kaggle competitions
- Knowledge of Reinforcement Learning
- Strong written and verbal communication skills
- Articulation skills
- Good team player
- Self-starter who requires minimal oversight
- Ability to prioritize and manage multiple tasks
- Process orientation and the ability to define and set up processes
PROJECTS THIS ROLE WILL SUPPORT
The role is expected to support in the domain of Digital Transformation engagements which requires client applications to provide their consumers with enhanced experience by transforming the digital capabilities. The clients are not from any specific industry though few have been listed to provide the perspective.
- Retail: The industry is focusing on improving sales and transitioning towards online market places. They also are looking out to build solutions to understand consumers better, design models and predict consumer likes / dislikes
- BFSI: Clients are looking digital transformation by taking almost all services online unless regulatory restrictions come in the way
- Travel and Hospitality: There is a lot of disruption happening in the domain as the market if quite competitive and the competition is cut throat. Topics such as in-venue experience, hyper personalization, mobility are driving lot of innovation
- Automobile: The industry is adopting transformation in both consumer and dealer’s digital enablement
- Healthcare: Exploring fresh ways to build patient data and derive insights. Build platforms to have real time tracking of patient’s health by consolidating data from multiple sources and devices and offer personalized medicines and treatments
- Telecom: The industry is on cusp of a tipping point moving from pure play voice services to data driven offerings. Telecom players are focusing on modernizing operations, digitizing services, network upgrades and redefining their strategic identity.
- Technology: Defining the future with digital transformation initiatives. Cloud Computing; IOT; Blockchain & AI are the current focus areas.
- Manufacturing: Currently in a world of uneasiness. The industry is innovating on adapting technology to run supply chains & operations, monetizing digitization, and leveraging data & analytics
- FMCG & CPG: Looking at cost cutting measures across all the operations. Strategizing with a more global outlook and looking at introducing products more aligned with consumer mindset
- Entertainment & Media: Industry moving towards a content oriented experience available across multiple distribution channels. User insights and newer content requires robust data solutions.
- Logistics & Shipping: Must explore newer technologies (robotics, real time delivery, self-driving vehicles & automated warehouses) and solutions to cater to consumer need and enhanced demands
- Insurance: Changing business and operating models. Enterprise Innovation Models redefining ways in why insurers collect information about consumers, discover coverage needs, identify target markets, integrate consumer data and rapidly respond to regulatory changes and compliance
- Education: The industry is automation a lot of paper workflows and taking them online along with providing enhanced user experience to attract the prospective customers
- Marketing: Increased focus on consumer experience. Build customer centric models and gather behavioural data about consumers to deliver personalized content
- Infrastructure & Real Estate: A fundamental shift in the consumer market – focus on environmental, social and financial concerns. Understanding consumer behavior is key to planning this year. Impact of data and analytics will begin to emerge, helping improve capacity planning and operational cost reduction.
- Energy & Utilities: Emerging energy services are threatening incumbents. Innovations in current technologies and exploring service based models.
POSSIBLE CAREER PATHS
Future growth areas in areas of Data Science and Analytics
Publicis Sapient is a digital transformation partner helping established organizations get to their future, digitallyenabled state, both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods, fusing strategy, consulting and customer experience with agile engineering and problem-solving creativity. As digital pioneers with 20,000 people and 53 offices around the globe, our experience spanning technology, data sciences, consulting and customer obsession – combined with our culture of curiosity and relentlessness – enables us to accelerate our clients’ businesses through designing the products and services their customers truly value. Publicis Sapient is the digital business transformation hub of Publicis Groupe. For more information, visit publicissapient.com