Job Description

Tecknoworks is a global technology consulting company. At our core, we embody values that define who we are and how we operate. We are curious, continuously seeking to expand our understanding and question conventional wisdom. Fearlessness drives us, propelling us to take daring steps to achieve significant outcomes. Our aspiration to be inspiring motivates us to consistently reach for our personal and collective best, setting an example for ourselves and those we interact with. Collaboration is our strength, capitalizing on the diverse brilliance within our team. Our commitment knows no bounds; we consistently go the extra mile to ensure enduring positive effects for our clients.

We are looking for a Data Scientist with solid experience in analytics and machine learning, particularly within AWS and Amazon SageMaker. You will work on end-to-end ML projects involving structured and unstructured data, developing scalable models and actionable insights for business stakeholders.

Depending on your seniority, you will either contribute as a strong individual contributor (Mid-Level) or drive architectural decisions, stakeholder alignment and mentoring (Senior).

Tecknoworks Context - What You Can Expect

• You’ll work in a cross-functional squad with Data Scientists, ML Engineers, Data Engineers, and Project Lead.
• Capacity to understand stakeholders, autonomy in execution, and collaborative problem-solving.
• Some project industries: Energetic, Life Sciences, FinTech and more.
• Tech ecosystem AWS and/or Azure cloud, plus Python and SQL.
• Delivery: outcome and quality driven.
• Access to senior mentorship and a structured growth path, supporting the development and communication skills. Also, we promote a growth mindset, empowering you to learn continuously and take ownership in solving complex, ambiguous problems.
• A consultant’s mindset and proactive attitude are essential; they allow you to foresee client requirements, spot opportunities, and provide concise, influential, data-based recommendations.
• Influence: Aligns multiple stakeholders and supports decision-making.

Requirements

• Perform advanced EDA, correlation analysis, and feature engineering on structured and text data;
• Develop churn prediction models using classification and/or survival analysis techniques;
• Handle class imbalance, calibrate decision thresholds, and design champion/challenger model frameworks;
• Apply interpretability techniques (SHAP, feature importance, PDPs) to identify key drivers and support business recommendations;
• Train, tune, and evaluate models using Amazon SageMaker (built-in algorithms or custom frameworks);
• Design decision-ready dashboards for business stakeholders;
• Define and track relevant KPIs;
• Deliver data-driven storytelling tailored to non-technical audiences;
• Experience with BI tools is considered a plus;
• Ensure data and model versioning, testing, and reproducibility;
• Implement data quality checks and validation logic;
• Support lightweight deployment and monitoring of ML models (batch or near real-time);
• Work with AWS services such as S3, Glue, Lambda, and SageMaker Pipelines;
• Step Functions or Airflow experience is a plus.

Qualifications

Mid-Level Expectations

• 3+ years' experience in data science with end-to-end ML delivery.
• Strong Python skills (pandas, scikit-learn).
• Solid SQL knowledge (preferably Redshift).
• Practical experience with AWS (S3, Glue, Lambda, SageMaker).
• Good communication skills and ability to work autonomously.
• Ability to translate data into clear insights for non-technical stakeholders

Senior-Level Expectations

• 5+ years' experience with advanced ML and solution ownership.
• Experience leading solution design, modelling strategy, and cross-team alignment.
• Ability to mentor junior/mid colleagues.
• Experience with ML workflow orchestration (SageMaker Pipelines, Airflow, Step Functions).
• Exposure complex pipelines and large-scale data architectures.
• Proven track record of influencing technical decisions

Nice-to-Have

• Previous exposure to energy sector industry (pricing models, contracts, switching behavior, seasonality, regulated price changes).
• Exposure to environments where clarity of thought, accountable execution, and thoughtful collaboration naturally shape how work gets done. Individuals who navigate complexity with a structured approach, treat outcomes with care, and remain open to refining their ideas through learning, and diverse perspectives tend to feel most at home in this role.

If you possess the ability to deconstruct complex problems into clear, actionable steps, demonstrate end-to-end ownership of deliverables, collaborate effectively with all stakeholders, uphold fairness and responsible machine learning practices. We look forward to your application.