We are seeking a Manager - Data Science in our fast paced & dynamic firm to lead a team of data scientists, the development and implementation of data-driven solutions and be a key driver in DS practice development. The ideal candidate will be responsible for delivering projects, managing, mentoring & building a team of data scientists, working closely with cross-functional teams to identify business problems and develop data-driven solutions, communicating findings and recommendations to clients and key stakeholders, and be a catalyst in driving practice development initiatives.
Role & responsibilities
Delivery & Project Management
- Work hands-on and lead the development and implementation of predictive models, data mining algorithms, and statistical analysis techniques.
- Work closely with the business and team to ensure projects are aligned to business goals.
- Enforce strong quality check for client deliverables and ensure delivery excellence.
- Collate stakeholder feedback, align on approaches, deliverables, roadmaps and get approval.
- Develop & own project plan including milestones, dates, owners, risks, contingency plans & documentation. Support the plan with clear and crisp communication.
- Collaborate and integrate with Data Engineering team to operationalize and deploy the models.
- Partner with technology and the business teams to build a superior data quality pipeline that will feed the models.
- Identify & implement opportunity of optimization and automation.
Practice Development
- Lead and be a catalyst in developing capabilities of BLEND360s Data Science practice.
- Partner with Data Science Practice Leads and clients to understand business problems, industry context, data sources, potential risks, and constraints and translate them into solutions.
- Provide industry specific expertise to build standard DS solutions along with establishing and maintaining strong relationship with clients.
- Own data science processes and tools; survey new developments within the data science space and adapt them within BLEND360.
- Create an ecosystem that fosters innovation and encourage members of the CoE to build innovative solutions and publish papers/content in public domain.
- Research and create intellectual property for the company that will benefit BLEND360 and its clients.
People Management
- Be a career advocate - define roles, responsibilities along with establishing direct accountabilities for direct reports to ensure delivery excellence & career growth.
- Drive Performance Management for team and establish various methods of feedback and monitoring.
- Formulates development plans and roadmaps for the team to help them succeed in their roles and grow at Blend360.
- Assists with the development and/or monitoring of workflow, procedures, and metrics to track employee and department productivity, gathers and analyses statistics and makes recommendations for performance improvement.
- 8+ Years of professional experience in Data Science Industry
- Ability to work Hands-on and manage multiple simultaneous projects. Should be able to work efficiently in team as well as an independent contributor.
- Expertise in key Data Science Domains such as, customer analytics (Acquisition modelling, recommendation engine, Segmentation, Lifetime Value, Loyalty, Retention), marketing analytics (MMM, MTA, Synthetics Control), Product & Pricing analytics
- Deep knowledge of variety of Machine Learning algorithms for Classification, Regression, forecasting, Clustering, NLP, LSTM, Optimization, and their real-world advantages/drawbacks
- Thorough knowledge of correlation/causation probability and stochastic processes, distributions, priors, and posteriors.
- Expertise with Data Science software languages (Python, SQL). Experience with PySpark, R, Scala and querying databases (Hadoop/Hive) is a plus
- Professional experience in developing solution on cloud-based platforms (Azure, GCP, AWS, Databricks)
- Experience in solving business problem for Retail, CPG, eCommerce, BFSI, Healthcare, Hospitality
- Through understanding of model lifecycle of cleansing/standardizing raw data, feature creation/selection, model build/rebuild/refresh.
- Develop and execute new and/or highly complex algorithms and statistical predictive models and determines analytical approaches and modelling techniques to evaluate potential future outcomes.
- Ability to work effectively in a global team and to be able to demonstrate the ability to communicate technical ideas and results to non-technical clients in written and verbal form.
- Proven ability to deploy machine learning models from the research environment (Jupyter Notebooks) to production via procedural- or pipeline-approaches.
- Experience with SQL and relational databases, query authoring (SQL) and tuning as well as working familiarity with a variety of databases including Hadoop/Hive.
- Ability to work independently with high energy, enthusiasm, and persistence.
- Exceptional problem-solving, analytical and organization skills with a detail-oriented attitude.
- Experience with Google Analytics, Adobe Analytics, Optimizely is a plus. Experience in digital marketing a plus
Educational Qualifications
Bachelor/masters degree in computer science, Computer Engineering, quantitative studies, such as Statistics, Math, Operation Research, Economics and Advanced Analytics
