Machine Learning Engineer
- Integration Minds
- 4 to 8 Yrs
- Bengaluru
- 4 years ago
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Job Description
Job Designation: ML Engineer
1.Purpose of Role
Clients North Americas Commercial Analytics is responsible for building competitive differentiated solutions that improve profitability, revenue or save costs in our Sales capabilities (assortment optimization, price and promo optimization, shelf-space, e-commerce to name a few). As a senior data scientist you will work at the intersection of
- methods in the realm of statistical/ econometric modelling and/or Machine Learning/Deep Learning techniques, best in class cloud technology & engineering and
- Use deep business expertise to solve real problems. As an added bonus, you will spend time to review on-going academic research in this area and work on applying them to your work.
- You will be instrumental in not only developing solutions that answer a business question, but also develop the expertise to put them in production and monitor the impact your work is having.
- What you will do
- Build custom ML representations to apply hierarchical regularization to learn custom representations in an open ended environment with the goal of inferring an internal representation matching unknown economic factors.
- Build validation frameworks to validate the internal ML representations against ground truth economic factors in realistic simulated environment, in order to enable objective metrics to a ML space not trivial to validate, and therefore ripe for distribution.
- Build ML systems as scalable, validated, tested, software systems to solve global-scale problems.
- You will work on building data science solutions that meet a certain threshold of rigor to solve business problems in the realm of assortment optimization, price and promotions, demand planning, supply and logistics, omni-channel analytics just to name a few.
- You will document your thought process and create artefacts that can be used to share with business for sign off
- You will be able to build code that creates reproducible results and is written as per teams design practices
- You will review methodology and code developed by your peers
- You will collaborate with other team members to advance teams ability to create quality solutions and move fast. You should be able to mentor/coach junior team members to continuously upskill them.
- You will design or influence creating KPI dashboards that track the quality of solutions and measure value
- You will communicate your results to the business in simple, explainable fashion that drives decision making
Who are we looking for
- Academic degree in, but not limited to, Masters or PhD in the following areas: Mathematics, Physics, Statistics, Economics, CS, IE, OR. Beyond academic degrees, we give more weightage to 5+ years (Masters) or 1+ years (PhD) of real world experience as a data scientist applying statistical/econometric and/or machine learning/deep learning methods to solve real business problems.
- Understanding of the ability to build custom ML representations from core academically tested building blocks.
- You should have master expertise in at least one of the following:
- Statistical/Econometric modelling which include but not limited to time series, regression methods, Bayesian statistics, non- parametric estimation methods
- Machine Learning/Deep Learning methods which include but not limited to Boosted and Bagging methods, Neural Nets, Deep Nets, NLP, Reinforcement Learning
- You should have at least 3 years of experience in feature engineering, training models, evaluate the effectiveness of models, set up of A/B tests (as necessary) and fine tune based on business feedback
- Experience in exploring data, hypothesis formulation, data wrangling that enriches understanding and creating clean data for analysis.
- You have above average experience in using Python for data science, visualization, and scripting. In addition, you also have experience to move code into production via version controls, PEP8 standards, writing docstrings, unit tests and creation of supporting artefacts.
- You have bias for action and make right trade-offs between analytical rigor and solving business needs
Technology skills
- You have above average experience in using Python for data science, visualization, and scripting. Experience with writing easily understood code along with docstrings, unit tests and supporting artefacts helps.
- You should be deeply familiar and comfortable with at least one autodifferentiation framework
- You have worked in a large cloud databases (any) and familiarity with distributed computing e.g. leverage Spark for large jobs.
- Experience in Github or alike tool for code versioning
- Intermediate or above expertise with SQL for querying and manipulating data
Few skills in addition that will make you stand out
- Experience to adopt software development best practices that scale your models into production
- Experience designing custom validation metrics and custom loss functions
Employement Category:
Employement Type: ContractIndustry: IT - SoftwareRole Category: Application Programming / MaintenanceFunctional Area: Not ApplicableRole/Responsibilies: Machine Learning EngineerContact Details:
Company: Integration MindsLocation(s): Bengaluru+ View Contact
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