Job Description

About us BLEND360 is an award-winning, new breed Data Science Solutions Company focused on powering exceptional results to our Fortune 500/1000 clients and other organizations. We are a hyper growth company - born at the intersection of advanced analytics, data and technology. BLEND360 is focused on their world-class people that help clients optimize business performance through data, technology and analytics. BLEND360 has more than 500+ employees with offices in NYC, MD, CO, CA, The Netherlands, and India. Blend360 continues to be one of the fastest growing companies, making the Inc. 5000 every year they have been in business. BLEND360 is known for our exceptional people, our get-it-done mentality, and delivering high impact and sustainable results. If you love to solve difficult problems and deliver results; if you like to learn new things and apply innovative, state-of-the-art methodology, join us at Home | Blend360 Summary: 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 practise 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 practise development initiatives. 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 BLEND360\'s 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. Desired Candidate Profile: 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/master\'s degree in computer science, Computer Engineering, quantitative studies, such as Statistics, Math, Operation Research, Economics and Advanced Analytics

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