Data Scientist / Machine Learning Engineer

Data Scientist / Machine Learning Engineer

Who We Are: We are a fast growing business and technology consultant company co-founded in 2019. We offer a custom-tailored, white-glove engineering service fit for our clients, because a digital transformation is more than just technology. With a successful track record of being a preferred vendor for Fortune 500 companies and as a trusted partner for some of the industry’s leading companies, our global talent has helped many clients achieve their goals.

The 3 G’s of RE:

“Get Shit Done.”

“Get Over Shit.”

“Give a Shit.”

Data Scientist / Machine Learning Engineer

Data is at the heart of everything we do, and as such, we are building a multi-disciplined data team to help us achieve our business goals. This Data Science/Machine Learning role will drive additional value for our customers by feeding into the delivery of strategic data science solutions whilst setting up resilient and future-proof ML infrastructure and engineering foundations. This role also exists to provide technical oversight of and direction for the design, development, and implementation of value-generating data science solutions across the business. At its core, this role will help build, train and deploy machine learning models as well as explore our data to find opportunities and features to support ML.

• Tech Stack (Must-Haves):
• Demonstrable experience of critical thinking, communication and problem-solving ability.
• Experience working in an e-commerce/retail market would be beneficial.
• Strong stakeholder management skills: working collaboratively with Data Science, System, DevOps, Data and Software Engineering teams.
• Extensive experience leading or delivering commercially driven Machine Learning projects from inception through to deployment and maintenance.
• Proven experience building Machine Learning projects in a Cloud-based data platform (AWS, MS Azure or GCP).
• Excellent communication and interpersonal skills, with the ability to translate complex technical concepts to non-technical stakeholders (Data Engineering to the Business)
• Extensive experience (5+ years) with Python and/or SQL
• Proven expertise and experience of Shallow ML frameworks – regression, classification, clustering; time series forecasting (prophet, ARIMA, SARIMA); dimensionality reduction approaches
• Proven experience in modern code development practices and implementation of MLOps strategies in the cloud to drive operational and infrastructure cost efficiencies.
• Knowledge of wider data warehousing, data architecture of data modelling concepts.
• Hands on experience designing, building, and maintaining ML infrastructure and taking ML models to production.
• Working knowledge of CI/CD practices.
• Tech Stack (Nice-to-Haves):
• Experience productionising recommender engines and ensemble ML in Google Cloud
• Experience or exposure to managing ML Infrastructure costs and operational reliability in the cloud.
• Willingness to learn new tools and techniques; proactively keeping up to date with latest thinking and practices in the data science space.
• Confident to challenge, and receptive to being challenged.
• Able to establish what does/doesn’t align to business/functional strategies/priorities and communicate dependencies clearly.
• Experience with the Google Cloud Stack (BigQuery, Dataform etc) as that is the main stack in play for this role
• Experience working with CI/CD pipelines through Github
• Experience working in a large data transformation / migration
• Knowledge of advanced analytics techniques, such as predictive modeling and machine learning
• Experience taking ML solutions into production, and exposure to data storage and processing within one of the three major cloud providers (GCP, Azure or AWS).
• Passionate about data science with the ability to articulate the potential value of the field in an evolving business landscape.
• Knowledge of Deep Learning techniques
• Able to establish what does/does not align to business/functional strategies/priorities and communicate dependencies clearly.
• Able to drive the adoption of best practice approaches to data science solution development, coaching, and supporting the wider data science team.
• Scope of Responsibility:
• Designing and developing our ML Operations (MLOps) infrastructure and practices to support the effective transition of machine learning models and PoCs into production.
• Working closely with business stakeholders to translate high-level business problems into the design of value-adding machine learning solutions and driving their implementation and adoption across the business
• Supporting machine learning model deployment into production and monitoring of the data science solutions lifecycle, including new and existing ML models post deployment.
• Designing, developing, and maintaining data science models and solutions, as well as explaining the concepts to non technical audiences.
• Implementing modern code development and MLOps strategies, in collaboration with Data Science and Data Engineering to support the proactive identification, targeting and resolution of any ML model(s) performance issues across their entire lifecycle.
• Developing operating procedures, work instructions and high-level designs of ML pipelines and architectures to support the effective documentation of our work.
• Developing an MLOps strategy aligned to best practice and existing DevOps practices in the company.
• Enhancing existing machine learning products and driving innovation through thought leadership, by staying abreast with market trends and novel research in this space.
• Embedding new machine learning solutions into the business through coaching, training, and providing experiment design oversight to data scientists.
• Working with third party partners and software providers to improve and/or implement new data science solutions and processes.
• Developing a strong knowledge of all data sources and maintaining relations with data users/processors across the business. Acting as a trusted advisor to business teams on data science and machine learning, bridging any gaps in understanding and literacy.

Join Our Global Team: We invite you to apply for the position at RE Partners. Join us in shaping the future of business technology consulting and transforming the way organizations thrive in a digital world. As a diverse, woman-owned global business, we pride ourselves on keeping talent happy – our 7% attrition rate speaks volumes. Bring your talented friends along and earn a referral bonus

Equal Opportunity Employer: We are an equal opportunity employer and welcome applications from all qualified individuals regardless of race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, or veteran status.

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