About the Role
Genpact is inviting applications for the role of AM, Machine Learning Expert - Data Science and Insights. The candidate should possess an MS in Mathematics, Computer Science, Information Systems, Computer Engineering, Systems Engineering, Computational Science, or Applied Engineering with 6+ years of relevant experience in Applied Machine Learning / Predictive Analytics. Exposure to Machine Learning & Quantitative Methods in Marketing / Consumer Behavior is essential. Full-cycle real-world Analytics project experience, from creating a Business use case, PA assessment/roadmap, Technology & Analytic Solutioning, Implementation, and Change Management, is highly desirable.
Responsibilities
This role will primarily focus on two areas:
- Project Lead/Delivery: Lead projects, set expectations with clients/stakeholders, and ensure successful execution.
- Solutioning: Conceptualize and develop relevant Predictive Analytic solutions for Analytic Customers. Envision opportunistic areas with clients by demonstrating relevant and credible Predictive Analytics solutions and paradigms. This may involve high-level assessment of customer Analytics readiness and creating associated analytic benchmarking, converging into a client-specific Predictive Analytics roadmap.
Key Roles and Responsibilities
The Manager/Senior Manager ML is expected to play a pivotal bridging role between statistical, technology specialists, AND business/functional resources. Broadly, the Manager/Senior Manager shall leverage their solutioning expertise to translate the customer’s business need into a techno-analytic problem and appropriately work with statistical & technology specialists to bring large-scale analytic solutions to fruition.
Key responsibilities include:
- Participate in SME reviews of Predictive Analytics opportunities/engagements.
- Project Delivery: Successful delivery of projects involving data Pre-processing, Model Training and Evaluation, Parameter Tuning.
- Manage Stakeholder/Customer Expectations.
- Project Blue Printing and Project Documentation.
- Creating Project Plan.
- Jump-start Machine Learning projects with customers, focusing on providing disruptive insights in reasonable timeframes.
- Actively collaborate with competency leaders in Big Data, OR, BI areas to stitch big ticket solutions with end-to-end span.
Required and Preferred Skills
Specific Competencies – Essential
Technology
- Exposure to Statistical Toolkits such as R, Weka, S-Plus, Matlab, SAS.
- Very good Python/R programming skills. Java programming skills are a plus.
- Direct involvement in working with large volumes of data and building, deploying, and measuring predictive analytics models (i.e., SVM, decision tree, clustering, logistic regression, linear and non-linear regression).
- Deep learning frameworks such as TensorFlow, Keras, Torch, Theano.
Specific Competencies – Desirable
Technology
- Understanding of GraphDB and tools such as Neo4j etc.
- Understanding of NLP, NLU, and Machine learning/Deep learning methods.
- SQL/NoSQL, MS Access, databases.
- UI development paradigms that would enable Text Mining Insights Visualization, e.g., Adobe Flex Builder, HTML5, CSS3.
- Linux, GPU Experience.
- Spark, Scala for distributed computing.
Methodology
- Previous experience with Big Data analytics implementations, using either Vanilla Hadoop or Cloudera/IBM BigInsights.
- Ability to Prioritize, Consultative mindset & Time management skills.
- Understanding/experience with the Google Cloud Platform/AWS/Azure and other Big Data solutions such as Cloudera is preferred.