{"id":2771334,"url":"https://alion.io/job/d-square-consulting-services-senior-data-scientist-artificial-intelligencemachine-learning","title":"Senior Data Scientist - Artificial Intelligence/Machine Learning","company":{"id":3800293,"name":"D Square Consulting Services","domain":"dsquareconsulting.com","url":"https://alion.io/company/d-square-consulting-services","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":46000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":71},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Embeddings","optional":false},{"name":"Keras","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"XGBoost","optional":false},{"name":"AWS","optional":true},{"name":"CI/CD","optional":true},{"name":"Feature Store","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"PyTorch","optional":true},{"name":"Snowflake","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-08-19T05:08:30Z","employer_posted_date":null,"last_verified_at":"2026-08-19T05:08:30Z","board_verified":false,"closed_at":null,"days_open":63,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":63},"description":"Job Description : Senior Data Scientist (AI/ML).\n\nExperience : 5-7 Years.\n\nWork mode : On-site.\n\nLocation : Bangalore.\n\nJob Summary : \n\nWe are looking for a Senior Data Scientist to join the team. The role focuses on developing, validating, and deploying machine learning and generative AI solutions to optimize omnichannel communications for marketing and advertising. You will partner with business stakeholders and engineering teams to translate use cases into scalable models, produce MLOps pipelines, and continuously monitor and improve model performance to drive measurable business impact.\n\nMust-have skills : \n\n- 5-7 years overall experience in analytics, data mining, machine learning, and deep learning.\n\n- Strong proficiency in Python and SQL.\n\n- Experience with model development using scikit-learn, TensorFlow, Keras, and XGBoost (or equivalents).\n\n- Practical exposure to MLOps : deployment, monitoring, and lifecycle management in production.\n\n- Working knowledge of relational databases and SQL-based data workflows.\n\n- Hands-on familiarity with generative AI/LLM concepts and implementation (prompting, embeddings, RAG).\n\n- Experience calling and integrating LLM APIs (e.g., OpenAI, Azure OpenAI) for business solutions.\n\n- Solid business acumen with the ability to translate modeling into measurable marketing/ad outcomes.\n\n- Should be flexible to work with US stakeholders in evening India hours ~ 11 pm IST.\n\n- Excellent communication and stakeholder collaboration skills.\n\nGood to have skills : \n\n- Experience in online media, marketing attribution, adtech ecosystems, or omnichannel marketing optimization.\n\n- Experience with big-data platforms and distributed processing : Apache Spark, SparkML.\n\n- Familiarity with Snowflake and AWS cloud services.\n\n- Experience with evaluation frameworks for generative models and automated quality checks.\n\n- Exposure to production data engineering practices, feature stores, or model governance.\n\n- Prior experience working across time zones with US-based teams.\n\nKey Responsibilities : \n\n- Partner with business stakeholders to identify, prioritize, and scope data science initiatives that deliver measurable marketing/advertising value, including GenAI-driven opportunities.\n\n- Design, build, validate, and productionize supervised and unsupervised ML models and generative AI solutions to optimize omnichannel communications and customer engagement.\n\n- Implement MLOps best practices : CI/CD for models, containerized deployments, monitoring, drift detection, and model refresh workflows.\n\n- Develop and maintain robust data pipelines, feature engineering processes, and model validation/testing frameworks.\n\n- Apply modern GenAI techniques (embeddings, RAG, prompt engineering) to create scalable, reliable solutions for content personalization, summarization, intent detection, or other use cases.\n\n- Perform exploratory data analysis, implement quality checks, and produce actionable insights and KPIs for stakeholders.\n\n- Collaborate with cross-functional teams (engineering, product, vendors/suppliers) to review modeling work, integrate models into platforms, and ensure operational readiness.\n\n- Monitor model performance post-deployment, iterate on models and thresholds, and document model lineage and assumptions.\n\n- Produce clear 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