Shortlist is a recruitment technology startup operating primarily in India and Kenya, working with the aim of building great teams for organizations. The Shortlist team has created a novel product which helps companies source and screen high and mid-level talent, cutting through piles of resumes and getting rid of dead-end interviews. We use digitized cognitive and competency based tests, and conduct interviews that measure the actual ability to do a job, rather than relying just on CVs, thus holding a treasure of data beyond CVs that can help match candidates to better jobs and vice versa.
We have worked with over 500 clients across the globe, supporting the growth of vibrant startups, growing businesses, and enterprises. We have worked with companies like Shell, DHL, Ather, The Rockerfeller Foundation, Sunculture, mKopa, Dalberg, Uber eats etc., invested and operated, worked across fields like consumer internet, financial services, clean energy, etc. Some of us come from recruiting and HR backgrounds, and some of us don’t. All of us share a passion for unlocking potential. Check out our website HERE. Also check out the Shortlist page on Glassdoor
As the Lead Data Scientist for Shortlist, you will help the organization make data-driven strategic decisions. Your responsibilities will include:
-Developing & coding production-grade novel algorithms to build a recommendation engine to match great candidates to jobs they love.
-Create a vision and data product roadmap for Shortlist, build, mentor and manage a team of data engineers, data analysts and data scientists.
-Managing, developing, maintaining and marketing the business experimentation suite at Fractal
-Conducting research and prototyping innovations; data and requirements gathering; solution scoping and architecture; consulting clients and client facing teams on advanced statistical and machine learning problems, especially in the areas of marketing and designing experiments
-Testing various machine learning and analytical tools, especially in the big data space, to scale prototypes to production-grade systems.
-Provide solutions to: Customer Segmentation & Targeting, Propensity Modeling, Churn Modeling, Lifetime Value Estimation, Forecasting, Recommender Systems, Modeling Response to Incentives, Marketing Mix Optimization, Price Optimization
-Being a good learner, a good mentor, who inspires peers and team members to learn and expand their skill set, guiding them in the right direction.
At Shortlist, you’ll be working and leading a range of projects:
-Refine and develop recommendation engines
-Design projects and experiments for future offerings and features
-Turn those experiments into actionable conclusions based on the results
-Build models to understand our users and predict actions
-Design communication models catered to cohorts
-Present and share ongoing data with business owners and senior leadership
-Create and refine a personalization framework
You can work out of Kenya (Nairobi) or India (Bombay/Hyderabad) based on your preferences and our business requirements. You will be working with a high-performing, cross-cultural team, collaborating with all major stakeholders from the CTO, The Country Heads across both geographies, Product, Customer Care and Operations.
You will work closely with the CEO and Co-Founder, Paul Breloff
You can directly apply here- http://bit.ly/2VqN9MX
Does this sound like you?
-4+ years of demonstrable experience designing ML/statistical solutions/Big Data to complex business problems at scale.
-Proficiency in at least one of R or Python’s (preferred) data science stack.
-Proficiency in statistical/ML predictive techniques such as Regression, Bayesian methods, tree-based learners, SVM etc.
-Prior exposure to big data technologies like Hadoop, Spark, Hive, Pig, Sqoop etc.
-Thorough grasp on RDBMS and data management concepts as well as fluency in SQL scripting.
-Operating knowledge of cloud computing platforms (AWS, especially EMR, EC2, S3, and the AWS CLI)
-The familiarity of version control, GIT helps!
Tagged as: #spark, artificial intelligence, big data, data science, hadoop, lead data scientist, python, R, regression
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